40 results on '"spatial filtering"'
Search Results
2. dEchorate: a calibrated room impulse response dataset for echo-aware signal processing.
- Author
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Carlo, Diego Di, Tandeitnik, Pinchas, Foy, Cedrić, Bertin, Nancy, Deleforge, Antoine, and Gannot, Sharon
- Subjects
IMPULSE response ,SIGNAL processing ,SPEECH enhancement ,UTILITIES (Computer programs) ,MICROPHONE arrays - Abstract
This paper presents a new dataset of measured multichannel room impulse responses (RIRs) named dEchorate. It includes annotations of early echo timings and 3D positions of microphones, real sources, and image sources under different wall configurations in a cuboid room. These data provide a tool for benchmarking recent methods in echo-aware speech enhancement, room geometry estimation, RIR estimation, acoustic echo retrieval, microphone calibration, echo labeling, and reflector position estimation. The dataset is provided with software utilities to easily access, manipulate, and visualize the data as well as baseline methods for echo-related tasks. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
3. Novel Noise Reduction Methods
- Author
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Taulu, Samu, Simola, Juha, Nenonen, Jukka, Parkkonen, Lauri, Supek, Selma, editor, and Aine, Cheryl J., editor
- Published
- 2014
- Full Text
- View/download PDF
4. A Millimeter-Wave Partially Overlapped Beamforming-MIMO Receiver: Theory, Design, and Implementation.
- Author
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Mohammadnezhad, Hossein, Abedi, Razieh, and Heydari, Payam
- Subjects
- *
MIMO systems , *BEAMFORMING , *SIGNAL processing , *RADIO frequency , *MULTIPLEXING - Abstract
This paper presents an analysis and design of a partially overlapped beamforming-multiple-input multiple-output (MIMO) architecture capable of achieving higher beamforming and spatial multiplexing gains with lower number of elements compared to conventional architectures. As a proof of concept, a four-element beamforming-MIMO receiver (RX) covering 64-67-GHz frequency band (the FCC’s newly allocated 64–71-GHz frequency band for high-speed wireless links between small cells) enabling two-stream concurrent reception is designed and measured. By partitioning the RX elements into two clusters and partially overlapping these clusters to create two three-element beamformers, both phased array (coherent beamforming) as well as MIMO (spatial multiplexing) features are simultaneously acquired. 6-bit phase shifters with 360° phase control and 5-bit VGAs with 11-dB range are designed to enable steering of the two RX clusters toward two arbitrary angular locations corresponding to two users. Fabricated in a 130-nm SiGe BiCMOS process, the RX achieves a 30.15-dB maximum direct conversion gain and a 9.8-dB minimum noise figure across 548-MHz IF bandwidth. S-parameter-based array factor measurements verify spatial filtering of the interference and spatial multiplexing in this RX chip. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
5. Cortical Signal Suppression (CSS) for Detection of Subcortical Activity Using MEG and EEG.
- Author
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Samuelsson, John G., Khan, Sheraz, Sundaram, Padmavathi, Peled, Noam, and Hämäläinen, Matti S.
- Abstract
Magnetoencephalography (MEG) and electroencephalography (EEG) use non-invasive sensors to detect neural currents. Since the contribution of superficial neural sources to the measured M/EEG signals are orders-of-magnitude stronger than the contribution of subcortical sources, most MEG and EEG studies have focused on cortical activity. Subcortical structures, however, are centrally involved in both healthy brain function as well as in many neurological disorders such as Alzheimer's disease and Parkinson's disease. In this paper, we present a method that can separate and suppress the cortical signals while preserving the subcortical contributions to the M/EEG data. The resulting signal subspace of the data mainly originates from subcortical structures. Our method works by utilizing short-baseline planar gradiometers with short-sighted sensitivity distributions as reference sensors for cortical activity. Since the method is completely data-driven, forward and inverse modeling are not required. In this study, we use simulations and auditory steady state response experiments in a human subject to demonstrate that the method can remove the cortical signals while sparing the subcortical signals. We also test our method on MEG data recorded in an essential tremor patient with a deep brain stimulation implant and show how it can be used to reduce the DBS artifact in the MEG data by ~ 99.9% without affecting low frequency brain rhythms. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
6. A new method of image denoising based on cellular neural networks.
- Author
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Gangyi Hu and Sumeth Yuenyong
- Subjects
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SIGNAL denoising , *SIGNAL processing , *IMAGE denoising , *ARTIFICIAL neural networks , *ARTIFICIAL intelligence - Abstract
This paper presents an edge constraint adaptive filtering algorithm based on cellular neural networks for image denoising. In the process of designing the three templates separately in cellular neural networks, the control template references the advantage of spatial filtering denoising. It resembles a spatial domain denoising filter. The feedback template sets as a matrix which generated by a high pass filter to achieve edge preservation. The proposed method can not only achieve denoising, but also protect edges in an image. In the process of designing the threshold template, we use the different gray levels in an image to achieve the threshold adjustment adaptively. The experiment simulation results show that this algorithm is effective. Its denoising effect is much better than the mean filtering, median filtering, Gaussian filtering and the non local means method. And compared with the anisotropic diffusion algorithm, this algorithm is also better for the impulsive noise (salt & pepper noise), the Poisson noise and the comprehensive noise denoising .Due to the parallelism and possible hardware implementation of cellular neural network. It can achieve real time image denoising, which has a good application prospect. [ABSTRACT FROM AUTHOR]
- Published
- 2018
7. Multi-channel scan mode and imaging algorithm for synthetic aperture ladar.
- Author
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Guo, Liang, Xu, Qing, Li, Xiaozhen, Zeng, Xiaodong, Tang, Yu, and Xing, Mengdao
- Subjects
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WAVELENGTHS , *IMAGING systems , *AZIMUTH , *SIMULATION methods & models , *SIGNAL processing - Abstract
The tunable band of ladar which is limited by the velocity of the laser’s tunable component contradict with the pulse repetition frequency (PRF), in SAL. Meanwhile, the swath of SAL is small for the micro-meter wavelength. This paper gives a novel imaging mode of SAL, which combines multichannel technique and Scan mode SAL. This system makes full use of information of the space domain with multichannel, and removes the ambiguity of the frequency domain in the azimuth direction. And then, controls the beam to scan in different swathes for a better width of the imaging scene, which could lead to a reasonable resolution loss. In view of the ambiguity in Scan mode, SPECAN analysis is utilized to resolve the ambiguity. Finally, the simulation proves the validity of the given method. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
8. dEchorate: a Calibrated Room Impulse Response Dataset for Echo-aware Signal Processing
- Author
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Diego Di Carlo, Antoine Deleforge, Nancy Bertin, Cédric Foy, Sharon Gannot, Pinchas Tandeitnik, Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Bar-Ilan University [Israël], Unité Mixte de Recherche en Acoustique Environnementale (UMRAE ), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema)-Université Gustave Eiffel, Inria Nancy - Grand Est, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Acoustics and Ultrasonics ,Acoustic Echo Retrieval ,Microphone ,Computer science ,QC221-246 ,Room impulse response ,02 engineering and technology ,Impulse (physics) ,01 natural sciences ,Software ,Echo-aware signal processing ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Computer vision ,Electrical and Electronic Engineering ,Hardware_ARITHMETICANDLOGICSTRUCTURES ,010301 acoustics ,Impulse response ,Acoustic echoes ,[SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph] ,Signal processing ,[STAT.AP]Statistics [stat]/Applications [stat.AP] ,Cuboid ,business.industry ,Echo (computing) ,Acoustics. Sound ,020206 networking & telecommunications ,QA75.5-76.95 ,Audio database ,Microphone arrays ,Room Geometry Estimation ,Speech enhancement ,Spatial Filtering ,Electronic computers. Computer science ,Artificial intelligence ,business ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
This paper presents a new dataset of measured multichannel room impulse responses (RIRs) named dEchorate. It includes annotations of early echo timings and 3D positions of microphones, real sources, and image sources under different wall configurations in a cuboid room. These data provide a tool for benchmarking recent methods in echo-aware speech enhancement, room geometry estimation, RIR estimation, acoustic echo retrieval, microphone calibration, echo labeling, and reflector position estimation. The dataset is provided with software utilities to easily access, manipulate, and visualize the data as well as baseline methods for echo-related tasks.
- Published
- 2021
9. Enhancing Performance of SSVEP-Based Visual Acuity via Spatial Filtering
- Author
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Xiaowei Zheng, Guanghua Xu, Chengcheng Han, Peiyuan Tian, Kai Zhang, Renghao Liang, Yaguang Jia, Wenqiang Yan, Chenghang Du, and Sicong Zhang
- Subjects
Visual perception ,Visual acuity ,visual acuity ,spatial filtering ,media_common.quotation_subject ,Neurosciences. Biological psychiatry. Neuropsychiatry ,medicine ,Contrast (vision) ,Original Research ,canonical correlation analysis ,media_common ,Mathematics ,steady-state visual evoked potential ,multielectrode signals combination ,Signal processing ,Spatial filter ,business.industry ,General Neuroscience ,Pattern recognition ,Spatial frequency ,Artificial intelligence ,medicine.symptom ,Canonical correlation ,business ,Energy (signal processing) ,Neuroscience ,RC321-571 - Abstract
The purpose of this study was to enhance the performance of steady-state visual evoked potential (SSVEP)-based visual acuity assessment with spatial filtering methods. Using the vertical sinusoidal gratings at six spatial frequency steps as the visual stimuli for 11 subjects, SSVEPs were recorded from six occipital electrodes (O1, Oz, O2, PO3, POz, and PO4). Ten commonly used training-free spatial filtering methods, i.e., native combination (single-electrode), bipolar combination, Laplacian combination, average combination, common average reference (CAR), minimum energy combination (MEC), maximum contrast combination (MCC), canonical correlation analysis (CCA), multivariate synchronization index (MSI), and partial least squares (PLS), were compared for multielectrode signals combination in SSVEP visual acuity assessment by statistical analyses, e.g., Bland–Altman analysis and repeated-measures ANOVA. The SSVEP signal characteristics corresponding to each spatial filtering method were compared, determining the chosen spatial filtering methods of CCA and MSI with a higher performance than the native combination for further signal processing. After the visual acuity threshold estimation criterion, the agreement between the subjective Freiburg Visual Acuity and Contrast Test (FrACT) and SSVEP visual acuity for the native combination (0.253 logMAR), CCA (0.202 logMAR), and MSI (0.208 logMAR) was all good, and the difference between FrACT and SSVEP visual acuity was also all acceptable for the native combination (−0.095 logMAR), CCA (0.039 logMAR), and MSI (−0.080 logMAR), where CCA-based SSVEP visual acuity had the best performance and the native combination had the worst. The study proved that the performance of SSVEP-based visual acuity can be enhanced by spatial filtering methods of CCA and MSI and also recommended CCA as the spatial filtering method for multielectrode signals combination in SSVEP visual acuity assessment.
- Published
- 2021
10. Time-Varying Spectral Kurtosis: Generalization of Spectral Kurtosis for Local Damage Detection in Rotating Machines under Time-Varying Operating Conditions
- Author
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Jacek Wodecki
- Subjects
0209 industrial biotechnology ,Frequency response ,Computer science ,spatial filtering ,local damage detection ,02 engineering and technology ,TP1-1185 ,01 natural sciences ,Biochemistry ,Signal ,Article ,Analytical Chemistry ,020901 industrial engineering & automation ,0103 physical sciences ,Electrical and Electronic Engineering ,010301 acoustics ,Instrumentation ,Signal processing ,Noise (signal processing) ,kurtosis ,Chemical technology ,Bandwidth (signal processing) ,Filter (signal processing) ,time-frequency analysis ,Atomic and Molecular Physics, and Optics ,Filter design ,Frequency domain ,vibration ,Algorithm - Abstract
Vibration-based local damage detection in rotating machines (i.e., rolling element bearings) is typically a problem of detecting low-energy cyclic impulsive modulations in the measured signal. This can be challenging as both the amplitude of a single damage-related impulse and the distance between impulses might be changing in time. From the signal processing point of view, this means time varying regarding the the signal-to-noise ratio, location of information in the frequency domain, and loss of periodicity (this remains cyclic but not periodic). One of the many attempted approaches to this problem is filtration using custom filters derived in a data-driven fashion. One of the methods to obtain such filters is a selector approach, where the value of a certain statistic is calculated for individual frequency bands of a signal that results in the magnitude response of a filter. In this approach, each chosen statistic will yield different results, and the obtained filter will be focused on different frequency bands focusing on different behaviors. One of the most popular and powerful selectors is spectral kurtosis as popularized by Antoni, which uses kurtosis as an operational statistic. Unfortunately, after closer inspection, it is easy to notice that, although selectors can significantly enhance the signal, they accumulate a great deal of noise and other background content of signals, which occupies the space (or rather time) in between the impulses. Another disadvantage is that such filters are time-invariant, because, in the principle of their construction, they are not adaptive, and even slight changes in the signal yield suboptimal results either by missing relevant data when the conditions in the signal change (i.e., informative impulses widen in bandwidth), or by accumulating unnecessary noise when the relevant information is not present (in between impulses or in frequency bands that impulses no longer occupy). To address this issue, I propose generalization of the selector approach using the example of spectral kurtosis. This assumes creating a time-varying selector that can be seen as a spatial filter in the time-frequency domain. The time-varying SK (TVSK) is estimated for segments of the signal, and, instead of a vector of SK-based filter coefficients, one obtains a TVSK-based matrix of coefficients that takes into account the time-varying properties of the signal. The obtained structure is then binarized and used as a filter. The presented method is tested using a simulated signal as well as two real-life signals measured on heavy-duty bearings in two different types of machine.
- Published
- 2021
11. An Efficient Fast and Convergence-Controlled Algorithm for Sidelobes Simultaneous Reduction (SSR) and Spatial Filtering
- Author
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Yasser Albagory
- Subjects
Steady state (electronics) ,Spatial filter ,TK7800-8360 ,Computer Networks and Communications ,Orientation (computer vision) ,spatial filtering ,Radiation pattern ,evolutionary optimization techniques ,Beamwidth ,Reduction (complexity) ,Wavelength ,linear arrays ,tapered beamforming ,Hardware and Architecture ,Control and Systems Engineering ,Signal Processing ,Convergence (routing) ,sidelobe level reduction ,Electrical and Electronic Engineering ,Electronics ,Algorithm ,Mathematics - Abstract
In this paper, an efficient sidelobe levels (SLL) reduction and spatial filtering algorithm is proposed for linear one-dimensional arrays. In this algorithm, the sidelobes are beamspace processed simultaneously based on its orientation symmetry to achieve very deep SLL at much lower processing time compared with recent techniques and is denoted by the sidelobes simultaneous reduction (SSR) algorithm. The beamwidth increase due to SLL reduction is found to be the same as that resulting from the Dolph-Chebyshev window but at considerably lower average SLL at the same interelement spacing distance. The convergence of the proposed SSR algorithm can be controlled to guarantee the achievement of the required SLL with almost steady state behavior. On the other hand, the proposed SSR algorithm has been examined for spatial selective sidelobe filtering and has shown the capability to effectively reduce any angular range of the radiation pattern effectively. In addition, the controlled convergence capability of the proposed SSR algorithm allows it to work at any interelement spacing distance, which ranges from tenths to a few wavelength distances, and still provide very low SLL.
- Published
- 2021
12. An Adaptive Spatial Filter for User-Independent Single Trial Detection of Event-Related Potentials.
- Author
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Woehrle, Hendrik, Krell, Mario M., Kirchner, Elsa A., Kirchner, Frank, Straube, Sirko, and Kim, Su Kyoung
- Subjects
- *
ADAPTIVE filters , *EVOKED potentials (Electrophysiology) , *SIGNAL processing , *BRAIN-computer interfaces , *MACHINE learning - Abstract
Goal: Current brain–computer interfaces (BCIs) are usually based on various, often supervised, signal processing methods. The disadvantage of supervised methods is the requirement to calibrate them with recently acquired subject-specific training data. Here, we present a novel algorithm for dimensionality reduction (spatial filter), that is ideally suited for single-trial detection of event-related potentials (ERPs) and can be adapted online to a new subject to minimize or avoid calibration time. Methods: The algorithm is based on the well-known xDAWN filter, but uses generalized eigendecomposition to allow an incremental training by recursive least squares (RLS) updates of the filter coefficients. We analyze the effectiveness of the spatial filter in different transfer scenarios and combinations with adaptive classifiers. Results: The results show that it can compensate changes due to switching between different users, and therefore allows to reuse training data that has been previously recorded from other subjects. Conclusions: The presented approach allows to reduce or completely avoid a calibration phase and to instantly use the BCI system with only a minor decrease of performance. Significance: The novel filter can adapt a precomputed spatial filter to a new subject and make a BCI system user independent. [ABSTRACT FROM PUBLISHER]
- Published
- 2015
- Full Text
- View/download PDF
13. Simple Broadband Quasi-Optical Spatial Multiplexer in Substrate Integrated Technology.
- Author
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Gomez-Tornero, Jose Luis, Martinez-Ros, Alejandro Javier, Mercader-Pellicer, Salvador, and Goussetis, George
- Subjects
- *
BROADBAND antennas , *QUASIPARTICLES , *RECONFIGURABLE optical add-drop multiplexers , *SUBSTRATE integrated waveguides , *SIGNAL processing , *FREQUENCIES of oscillating systems - Abstract
We present a new type of broadband spectral-spatial quasi-optical decomposer for microwave analog signal processing fully implemented in substrate integrated waveguide (SIW) technology. An input SIW is modulated to couple energy to a near-field focused surface wave inside the hosting substrate. Due to its inherent spatially dispersive response, the focal point location varies with frequency. Thus, by placing output SIW ports at the appropriate positions, the focused signal can be extracted for each frequency providing instantaneous spectral decomposition. A design with six output channels from 11 to 16 GHz with 4-dB insertion losses and 1-ns group-delay swing is illustrated. Experiments on a prototype are reported to prove the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF
14. Analysis of the quantitative measurement for a lateral shear interferometer in a convergent beam mode using Fourier transform method.
- Author
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Joenathan, Charles, Bernal, Ashley, Youn Woonghee, Yanzeng Li, and Wanseok Oh
- Subjects
- *
SHEARING interferometers , *FOURIER transform optics , *HOLOGRAPHIC optical elements , *WAVEFRONTS (Optics) , *SIGNAL processing - Abstract
Lateral shear interferometry operating in the convergent beam mode has been used for testing optical components. This method is simple and phase information of the wavefront has conventionally been extracted using phase stepping techniques. We propose to use defocus, which introduces uniform tilt as a means of extracting phase information via two procedures, namely spatial phase stepping and spatial frequency carrier method. Experimental results are presented that show the wavefront phase extracted with defocus before and after the focal point of the lens. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
15. Concurrent Communication and Sensing in Cognitive Radio Devices: Challenges and an Enabling Solution.
- Author
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Tsakalaki, Elpiniki, Alrabadi, Osama N., Tatomirescu, Alexandru, de Carvalho, Elisabeth, and Pedersen, Gert F.
- Subjects
- *
COGNITIVE radio , *WIRELESS communications performance , *WIRELESS communications , *BEAMFORMING , *SIGNAL processing , *RADIO frequency - Abstract
Cognitive radios (CRs) need to continuously monitor the availability of unoccupied spectrum. Prior work on spectrum sensing mainly focused on time-slotted schemes where sensing and communication take place on different time periods in the same frequency. This however leads to a) limited CR throughput as data transmissions need to be interrupted for the sensing task, and b) unreliable detection performance since sensing happens in specific confined time durations. The paper describes the basic design challenges and hardware requirements that restrain CRs from simultaneously and continuously sensing the spectrum while transmitting in the same frequency band. The paper then describes a novel approach based on spatial filtering that promises to empower CRs with concurrent transmission and sensing capabilities. The idea is to equip the CR with redundant transmit antennas for forming an adaptive spatial filter that selectively nulls the transmit signal in the sensing direction. By doing so, a wideband isolation level of \sim 60 dB is obtained by the antenna system. Finally, by following the spatial filtering stage with active power cancellation in the radio-frequency stage and in the baseband stage, a total isolation in excess of a 100 dB required for enabling concurrent communication and sensing can be obtained. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
- Full Text
- View/download PDF
16. Lateral shear interferometer using multiplexed holographic lenses and spatial Fourier transform: varying spectrum position and phase fluctuations.
- Author
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Joenathan, Charles, Bernal, Ashley, and Sirohi, Rajpal S.
- Subjects
- *
FOURIER transforms , *HOLOGRAPHIC optical elements , *FOURIER transform optics , *SIGNAL processing , *BEAMFORMING , *INTERFEROMETRY - Abstract
Previously, we reported a simple method to obtain lateral shear in both the x- and y-directions using a multiplexing technique. The phase data was extracted using the inherent spatial carrier fringes formed due to the tilt in the two sheared beams. In this article, we report that an error in phase map is introduced when the band-pass-filtered Fourier transform (FT) spectrum is not centered prior to performing the inverse FT to obtain the phase. We also found that intentionally introducing aberrations when capturing dynamic fluctuations in the wave front, resulted in controlling the spread of the Fourier spectrum. [ABSTRACT FROM AUTHOR]
- Published
- 2013
- Full Text
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17. Local modal filters for automated data-based damage localization using ambient vibrations.
- Author
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Tondreau, G. and Deraemaeker, A.
- Subjects
- *
MODAL filtering , *CONTINUUM damage mechanics , *VIBRATION (Mechanics) , *SIGNAL processing , *STIFFNESS (Mechanics) , *TIME-domain analysis , *DATA analysis - Abstract
Abstract: The motivation of the paper is to develop a fully automated data-based technique for damage localization using in-service ambient vibrations. The idea is an extension of the modal filtering technique previously developed for damage detection. A very large network of dynamic strain sensors is deployed on the structure to be monitored and split into several independent local sensor networks. Simple and fast signal processing techniques are coupled to statistical control charts for efficient and fully automated damage localization. The efficiency of the method is demonstrated using time-domain simulated data on a simply supported beam and a three-dimensional bridge structure. The method is able to detect and locate very small damages (2% stiffness reduction in an area corresponding to 1/100th of the length of the structure) even in the presence of noise on the measurements and variability of the baseline structure. [Copyright &y& Elsevier]
- Published
- 2013
- Full Text
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18. Near-Field Spherical Microphone Array Processing With Radial Filtering.
- Author
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Fisher, Etan and Rafaely, Boaz
- Subjects
MICROPHONE arrays ,HARMONIC analysis (Mathematics) ,CHEBYSHEV approximation ,SIGNAL processing ,BESSEL functions ,POLYNOMIALS ,BEAMFORMING - Abstract
This paper presents an analysis of spherical microphone array capabilities in the near-field, with an emphasis on radial filtering of sources in a given direction. The near-field of the array is defined in terms of frequency and distance from the array. Directional beamforming is demonstrated given the near-field radial compensation filter, which yields a desired directional beampattern at a chosen distance from the array. This pattern deteriorates as the source draws away from the array. Next, a framework is presented for radial filter design, enabling distance discrimination between sources positioned in the same direction relative to the array. Design examples include Dolph–Chebyshev radial filtering, radial notch filtering, and numerical design. Performance is analyzed in terms of spatial response and robustness to noise. Results show radial filtering is practical for improving attenuation of far-field and near-field interfering sources relative to a desired source positioned in the same direction. [ABSTRACT FROM PUBLISHER]
- Published
- 2011
- Full Text
- View/download PDF
19. Spatial Filtering of MEG Signals for User-Specified Spherical Regions.
- Author
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Özkurt, Tolga Esat, Mingui Sun, Wenyan Jia, and Sclabassi, Robert J.
- Subjects
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BEAMFORMING , *PARTIAL differential equations , *BESSEL functions , *SIGNAL processing , *HARMONIC functions - Abstract
We introduce a spatial filtering method in the spherical harmonics domain for constraining magnetoencephalographic (MEG) multichannel measurements to any user-specified spherical region of interest (ROl) inside the head. The method relies on a linear transformation of the signal space separation inner coefficients that represent the MEG signal generated by sources located inside the head. The spatial filtering is achieved effectively by constructing a spherical harmonics basis vector that is dependent on the center of the targeted ROI and it does not require any discrete division of the headspace into grids like the traditional MEG spatial filtering approaches. The validation and the performance of the method are demonstrated through both simulated and actual bilateral auditory-evoked data experiments. [ABSTRACT FROM AUTHOR]
- Published
- 2009
- Full Text
- View/download PDF
20. Escalamiento de la ecuación de Burgers.
- Author
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Aldama, Álvaro A., Mejía, Miguel Á., and Beckie, Roger
- Subjects
BURGERS' equation ,REYNOLDS number ,TURBULENCE ,HEAT equation ,BEAMFORMING ,SIGNAL processing ,SCALING (Social sciences) ,LEVEL of measurement ,COMPUTER simulation - Abstract
Copyright of Ingeniería Hidráulica en México is the property of Instituto Mexicano de Tecnologia del Agua (IMTA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2009
21. Implementation of Novel Algorithms for Smart Antenna.
- Author
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Bidkar, G. A. and Hunagund, P. V.
- Subjects
- *
ANTENNA array design & construction , *BEAMFORMING , *ALGORITHMS , *DIVERSITY receiving systems , *SYNCHRONIZATION , *CALIBRATION , *HARDWARE , *SIGNAL processing ,MATLAB (Bangladesh) - Abstract
A smart antenna is an antenna array system aided by some 'smart' algorithm designed to adapt to different signal environments. Smart antennas mitigate the problem of fading through diversity reception and beamforming, while minimizing interference through spatial filtering. For both switched beam and fully adaptive arrays, a myriad of algorithms have been developed to extract wireless signals from a variety of environments. The performance of a particular smart antenna system depends on how well-suited a chosen adaptive algorithm is to its operating signal environment. The best algorithm for a particular array system must, not only account for the signal environment at hand, but also for a number of other practical considerations, including synchronization, the presence or absence of carrier offsets, the reliability of array calibration data, and hardware cost. In this paper, the implementation of popular adaptive algorithms, namely LMS and RLS algorithms in MATLAB, along with the corresponding results, have been presented. [ABSTRACT FROM AUTHOR]
- Published
- 2009
22. Entropy-Based Optimization of Wavelet Spatial Filters.
- Author
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Farina, Dario, Nlandu Kamavuako, Ernest, Jian Wu, and Naddeo, Francesco
- Subjects
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SIGNAL processing , *CONTROL theory (Engineering) , *WAVELETS (Mathematics) , *ENTROPY , *FILTERS (Mathematics) , *SYSTEMS theory , *MOTOR unit , *ELECTROPHYSIOLOGY , *ELECTRIC resistors - Abstract
A new class of spatial filters for surface electromyo- graphic (EMG) signal detection is proposed. These filters are based on the 2-D spatial wavelet decomposition of the surface EMG recorded with a grid of electrodes and inverse transformation after zeroing a subset of the transformation coefficients. The filter transfer function depends on the selected mother wavelet in the two spatial directions. Wavelet parameterization is pro- posed with the aim of signal-based optimization of the transfer function of the spatial filter. The optimization criterion was the minimization of the entropy of the time samples of the output signal. The optimized spatial ifiter is linear and space invariant. In simulated and experimental recordings, the optimized wavelet ifiter showed increased selectivity with respect to previously proposed filters. For example, in simulation, the ratio between the peak-to-peak amplitude of action potentials generated by motor units 200 apart in the transversal direction was 8.58% (with monopolar recording), 2.47% (double differential), 2.59% (normal double differential), and 0.47% (optimized wavelet filter). In experimental recordings, the duration of the detected action potentials decreased from (mean ± SD) 6.9 ± 0.3 ms (monopolar recording), to 45 ± 0.2 ms (normal double differential), 3.7 ± 0.2 ms (double differential), and 3.0 ± 0.1 ms (optimized wavelet filter). In conclusion, the new class of spatial filters with the proposed signal-based optimization of the transfer function allows better discrimination of individual motor unit activities in surface EMG recordings than it was previously possible. [ABSTRACT FROM AUTHOR]
- Published
- 2008
- Full Text
- View/download PDF
23. ABOUT SPATIAL FILTERING RESPONSES OF THE BOUGUER GRAVITY ANOMALIES MAP OF THE NORTH OF MOROCCO.
- Author
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Bakkali, Saad, Amrani, Mahacine, and Bahi, Lahcen
- Subjects
- *
GRAVIMETRY , *GRAVITY anomalies , *SIGNAL processing , *AERIAL surveys - Abstract
This paper reports the results and interpretations of gravity signatures of the transformed map of Bouguer gravity anomalies of the Tangier-Tetuan area according with the data provided by aerial and terrestrial gravimetric surveys carried out in that area. Filtering analysis based on classic signal process was applied. Operators signal process like vertical gradient, horizontal gradient and downward continuation were used. This study also brings the possibility to define other adequate methods under consideration for the analysis of the gravity of the Tangier-Tetuan area. [ABSTRACT FROM AUTHOR]
- Published
- 2007
24. Estimation of Motor Unit Conduction Velocity From Surface EMG Recordings by Signal-Based Selection of the Spatial Filters.
- Author
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Mesin, Luca, Tizzani, Francesca, and Farina, Dario
- Subjects
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MUSCLES , *MOTOR unit , *ELECTROMAGNETISM , *SIGNAL processing , *SIMULATION methods & models , *ELECTRODES - Abstract
Muscle fiber conduction velocity (CV) can be estimated by the application of a pair of spatial filters to surface electromagnetic (EMG) signals and compensation of the spatial filter transfer function with equivalent temporal filters. This method integrates the selection of the spatial filters for signal detection to the estimation of CV. Using this approach, in this paper, we propose a novel technique for signal-based selection of the spatial filter pair that minimizes the effect of nonpropagating signal components (end-of-fiber effects) on CV estimates (optimal filters). The technique is applicable to signals with one propagating and one nonpropagating component, such as single motor unit action potentials. It is shown that the determination of the optimal filters also allows the identification of the propagating and nonpropagating signal components. The new method was applied to simulated and experimental EMG signals. Simulated signals were generated by a cylindrical, layered volume conductor model. Experimental signals were recorded from the abductor pollicis brevis with a linear array of 16 electrodes. In the simulations, the proposed approach provided CV estimates with lower bias due to nonpropagating signal components than previously proposed methods based on the entire signal waveform. In the experimental signals, the technique separated propagating and nonpropagating signal components with an average reconstruction error of 2.9 ± 0.9% of the signal energy. The technique may find application in single motor unit studies for decreasing the variability and bias of CV estimates due to the presence and different weights of the nonpropagating components. [ABSTRACT FROM AUTHOR]
- Published
- 2006
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25. MEG and EEG Source Localization in Beamspace.
- Author
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Rodríguez-Rivera, Alberto, Baryshnikov, Boris V., van Veen, Barry D., and Wakai, Ronald T.
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SIGNAL processing , *ALGORITHMS , *ELECTROENCEPHALOGRAPHY , *SOMATOSENSORY evoked potentials , *DIFFERENCES , *QUANTITATIVE research - Abstract
Beams pace methods are applied to EEG/MEG source localization problems in this paper. Beamspace processing involves passing the data through a linear transformation that reduces the data dimension prior to applying a desired statistical signal processing algorithm. This process generally reduces the data requirements of the subsequent algorithm. We present one approach for designing beamspace transformations that are optimized to preserve source activity located within a given region of interest and show that substantial reductions in dimension are obtained with negligible signal loss. Beamspace versions of maximum likelihood dipole fitting, MUSIC, and minimum variance beamforming source localization algorithms are presented. The performance improvement offered by the beamspace approach with limited data is demonstrated by bootstrapping somatosensory data to evaluate the variability of the source location estimates obtained with each algorithm. The quantitative benefits of beamspace processing depend on the algorithm, signal to noise ratio, and amount of data. Dramatic performance improvements are obtained in scenarios with low signal to noise ratio and a small number of independent data samples. [ABSTRACT FROM AUTHOR]
- Published
- 2006
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26. Influence of muscle fibre shortening on estimates of conduction velocity and spectral frequencies from surface electromyographic signals.
- Author
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Schulte, E., Farina, D., Merletti, R., Rau, G., and Disselhorst-Klug, C.
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ELECTROMYOGRAPHY , *ELECTRODIAGNOSIS , *MUSCLE contraction , *ELECTROPHYSIOLOGY , *PHYSIOLOGY , *MUSCLES , *MATHEMATICAL models , *SKELETAL muscle physiology , *BIOLOGICAL models , *COMPARATIVE studies , *ELECTRODES , *RESEARCH methodology , *MEDICAL cooperation , *NEURAL conduction , *RESEARCH , *SIGNAL processing , *EVALUATION research - Abstract
The study of surface electromyographic (EMG) signals under dynamic contractions is becoming increasingly important. However, knowledge of the methodological issues that may affect such analysis is still limited. The aim of the study was to analyse the effect of fibre shortening on estimates of conduction velocity (CV) and mean power spectral frequency (MNF) from surface EMG signals. Single fibre action potentials were simulated, as detected by commonly used spatial filters, for different fibre lengths. No physiological modifications were included with changes in fibre length, and thus only geometrical artifacts related to fibre shortening were investigated. The simulation results showed that the dependence of CV and MNF on fibre shortening is affected by the fibre location, electrode position and the spatial filter applied. With shortening of up to 50% for a fibre of 50 mm semi-length, the variations in CV and MNF estimates with shortening in bipolar recordings were 0.5% (CV) and 0.7% (MNF) for superficial fibres, and 3.6% and 5.1% for deeper fibres. Using the longitudinal double differential filter, under the same conditions, the percent variation was 0% and 0.2%, and 24.7% and 15.8%, respectively. The main conclusions were, first, muscle fibre shortening can significantly affect estimates of CV and MNF, especially for short fibre lengths. However, for long (semi-length >50 mm) and superficial fibres, this effect is limited for shortenings of up to 50% of the initial fibre length. Secondly, CV and MNF are almost equally affected by changes in muscle length; and, thirdly, sensitivity to fibre shortening depends on the spatial filter applied for signal detection. [ABSTRACT FROM AUTHOR]
- Published
- 2004
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27. Brain-Computer Interfaces using Machine Learning
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Papadopoulos,Theodoros and Varlamis,Iraklis
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Machine Learning ,Smart Home ,Brain-Computer Interface ,Spatial Filtering ,Signal Processing ,Electroencephalography ,Amazon Alexa - Abstract
This thesis explores machine learning models for the analysis and classification of electroencephalographic (EEG) signals used in Brain-Computer Interface (BCI) systems. The goal is 1) to develop a system that allows users to control home-automation devices using their mind, and 2) to investigate whether it is possible to achieve this, using low-cost EEG equipment. The thesis includes both a theoretical and a practical part. In the theoretical part, we overview the underlying principles of Brain-Computer Interface systems, as well as, different approaches for the interpretation and the classification of brain signals. We also discuss the emergent launch of low-cost EEG equipment on the market and its use beyond clinical research. We then dive into more technical details that involve signal processing and classification of EEG patterns using machine leaning. Purpose of the practical part is to create a brain-computer interface that will be able to control a smart home environment. As a first step, we investigate the generalizability of different classification methods, conducting a preliminary study on two public datasets of brain encephalographic data. The obtained accuracy level of classification on 9 different subjects was similar and, in some cases, superior to the reported state of the art. Having achieved relatively good offline classification results during our study, we move on to the last part, designing and implementing an online BCI system using Python. Our system consists of three modules. The first module communicates with the MUSE (a low-cost EEG device) to acquire the EEG signals in real time, the second module process those signals using machine learning techniques and trains a learning model. The model is used by the third module, that takes control of cloud-based home automation devices. Experiments using the MUSE resulted in significantly lower classification results and revealed the limitations of the low-cost EEG signal acquisition device for online BCIs.  
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- 2019
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28. Spatial Filtering of RF Interference in Radio Astronomy Using a Reference Antenna Array
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Albert-Jan Boonstra, Alle-Jan van der Veen, Ahmad Mouri Sardarabadi, and Astronomy
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Covariance matrices ,Computer science ,spatial filtering ,Smart antenna ,02 engineering and technology ,radio astronomy ,Interference (wave propagation) ,01 natural sciences ,Electromagnetic interference ,Sensor array ,reference antenna ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Antenna arrays ,Electrical and Electronic Engineering ,Arrays ,010303 astronomy & astrophysics ,Computer Science::Information Theory ,Spatial filter ,business.industry ,interference cancellation ,Astrophysics::Instrumentation and Methods for Astrophysics ,020206 networking & telecommunications ,Single antenna interference cancellation ,Array signal processing ,Signal Processing ,Reference antenna ,Interference ,Noise ,Signal processing algorithms ,Telecommunications ,business ,Telescopes ,Radio astronomy - Abstract
Radio astronomical observations are increasingly contaminated by RF interference. Assuming an array of telescopes, a previous technique considered spatial filtering based on projecting out the interferer array signature vector. A disadvantage is that this effectively reduces the array by one (expensive) telescope. In this paper, we consider extending the astronomical array with a reference antenna array, and develop spatial filtering algorithms for this situation. The information from the reference antennas improves the quality of the interferer signature vector estimation, hence more of the interference can be projected out. Moreover, since only the covariance data of the astronomical array has to be reconstructed, the conditioning of the problem improves as well. The algorithms are tested both on simulated and experimental data.
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- 2016
29. A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update
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Florian Yger, Laurent Bougrain, Alain Rakotomamonjy, Andrzej Cichocki, Fabien Lotte, Maureen Clerc, Marco Congedo, Popular interaction with 3d content (Potioc), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), RIKEN Center for Brain Science [Wako] (RIKEN CBS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Analysis and modeling of neural systems by a system neuroscience approach (NEUROSYS), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Skolkovo Institute of Science and Technology [Moscow] (Skoltech), Nicolaus Copernicus University [Toruń], Computational Imaging of the Central Nervous System (ATHENA), Inria Sophia Antipolis - Méditerranée (CRISAM), GIPSA - Vision and Brain Signal Processing (GIPSA-VIBS), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Equipe Apprentissage (DocApp - LITIS), Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Université Le Havre Normandie (ULH), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA), Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision (LAMSADE), Université Paris Dauphine-PSL, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), and Normandie Université (NU)
- Subjects
Signal processing ,Time Factors ,Computer science ,Feature extraction ,Biomedical Engineering ,02 engineering and technology ,Adaptive classifiers ,Tensors ,Machine learning ,computer.software_genre ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,0302 clinical medicine ,[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] ,0202 electrical engineering, electronic engineering, information engineering ,Animals ,Humans ,EEG ,Riemannian geometry ,BCI ,Brain–computer interface ,Spatial filtering ,business.industry ,Deep learning ,Brain ,[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] ,Signal Processing, Computer-Assisted ,Electroencephalography ,Linear discriminant analysis ,Classification ,Random forest ,Transfer learning ,Statistical classification ,ComputingMethodologies_PATTERNRECOGNITION ,Brain-Computer Interfaces ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,Transfer of learning ,computer ,Classifier (UML) ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing ,Algorithms ,030217 neurology & neurosurgery - Abstract
International audience; Objective: Most current Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately 10 years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. Approach: We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. Main results: We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. Significance: This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these Review of Classification Algorithms for EEG-based BCI 2 methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.
- Published
- 2018
30. Spatial filtering for enhanced high-density surface electromyographic examination of neuromuscular changes and its application to spinal cord injury.
- Author
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Zhang, Xu, Li, Xinhui, Tang, Xiao, Chen, Xun, Chen, Xiang, and Zhou, Ping
- Subjects
- *
SPATIAL filters , *SPINAL cord injuries , *PARALYSIS , *NONNEGATIVE matrices , *MATRIX decomposition , *RESEARCH , *SKELETAL muscle , *RESEARCH methodology , *MEDICAL cooperation , *EVALUATION research , *COMPARATIVE studies , *SIGNAL processing , *FACTOR analysis , *ELECTROMYOGRAPHY , *CLUSTER analysis (Statistics) , *ALGORITHMS - Abstract
Background: Spatial filtering of multi-channel signals is considered to be an effective pre-processing approach for improving signal-to-noise ratio. The use of spatial filtering for preprocessing high-density (HD) surface electromyogram (sEMG) helps to extract critical spatial information, but its application to non-invasive examination of neuromuscular changes have not been well investigated.Methods: Aimed at evaluating how spatial filtering can facilitate examination of muscle paralysis, three different spatial filtering methods are presented using principle component analysis (PCA) algorithm, non-negative matrix factorization (NMF) algorithm, and both combination, respectively. Their performance was evaluated in terms of diagnostic power, through HD-sEMG clustering index (CI) analysis of neuromuscular changes in paralyzed muscles following spinal cord injury (SCI).Results: The experimental results showed that: (1) The CI analysis of conventional single-channel sEMG can reveal complex neuromuscular changes in paralyzed muscles following SCI, and its diagnostic power has been confirmed to be characterized by the variance of Z scores; (2) the diagnostic power was highly dependent on the location of sEMG recording channel. Directly averaging the CI diagnostic indicators over channels just reached a medium level of the diagnostic power; (3) the use of either PCA-based or NMF-based filtering method yielded a greater diagnostic power, and their combination could even enhance the diagnostic power significantly.Conclusions: This study not only presents an essential preprocessing approach for improving diagnostic power of HD-sEMG, but also helps to develop a standard sEMG preprocessing pipeline, thus promoting its widespread application. [ABSTRACT FROM AUTHOR]- Published
- 2020
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31. Dual polarization beamforming algorithm for multipath mitigation in {GNSS}
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Josef A. Nossek, Matteo Sgammini, Felix Antreich, Friederike Fohlmeister, and Andreas Iliopoulos
- Subjects
020301 aerospace & aeronautics ,Spatial correlation ,Multipath mitigation ,Spatial filtering ,Covariance function ,Computer science ,Estimation theory ,Estimator ,020206 networking & telecommunications ,02 engineering and technology ,Delay spread ,Antenna array ,0203 mechanical engineering ,Control and Systems Engineering ,Signal Processing ,Computer Science::Networking and Internet Architecture ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Rake receiver ,Computer Vision and Pattern Recognition ,Electrical and Electronic Engineering ,Software ,Multipath propagation ,Computer Science::Information Theory - Abstract
A multipath mitigation technique for GNSS is proposed.The technique exploites the change of polarization when a signal is reflected.A novel statistic based on the outputs of a correlator bank is introduced to estimate the multipath DoA and polarization.Applying the technique increases the estimation performance in the case of highly temporally or spatially correlated multipath and line-of-sight signal. This paper treats the problem of line-of-sight (LOS) parameter estimation in strong multipath environments. In the case of highly temporally and spatially correlated LOS and multipath signals, such as urban canyons, common multipath mitigation methods are highly degraded, as signal separation cannot be performed in the spatio temporal domain. In this case, we exploit the LOS and multipath polarization diversity to decouple the signals using an antenna array with right-hand-circular polarization (RHCP) and left-hand-circular polarization (LHCP) feeds. The multipath direction- of-arrival (DOA) and polarization coefficients can effectively be estimated from the LHCP spatial covariance matrix. The LOS DOA can be estimated from the RHCP spatial covariance matrix. The spatial covariance matrices are calculated from the outputs of a matched correlator bank. The DOA and polarization estimates are used to implement a dual polarization beamformer, which maximizes the LOS energy and suppresses multipath energy over both polarizations. The LOS time-delay is estimated from the beamformer output with a maximum-likelihood estimator with a significantly reduced number of parameters and computational complexity in comparison to a full model estimator. Simulation results for GPS show that the proposed dual polarization beamforming algorithm performs better than an equivalent single-polarization beamformer in a dense multipath environment.
- Published
- 2017
32. Optimal linear spatial filters for event-related potentials based on a spatio-temporal model: Asymptotical performance analysis
- Author
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Bertrand Rivet, Antoine Souloumiac, GIPSA - Vision and Brain Signal Processing (GIPSA-VIBS), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), GIPSA-Services ( GIPSA-Services ), Grenoble Images Parole Signal Automatique ( GIPSA-lab ), Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ), Département Métrologie Instrumentation & Information ( DM2I ), Laboratoire d'Intégration des Systèmes et des Technologies ( LIST ), Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay, Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Laboratoire Outils d'Analyse des Données (LOAD), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay
- Subjects
[ MATH ] Mathematics [math] ,Asymptotically optimal algorithm ,[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing ,Computer science ,0206 medical engineering ,Biomedical signal processing ,spectrum analysis ,Independent component analysis ,02 engineering and technology ,Interference (communication) ,Stimulus (physiology) ,P300 speller ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,Event-related potential ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,[ INFO.INFO-DS ] Computer Science [cs]/Data Structures and Algorithms [cs.DS] ,Spatial filtering ,Spatial filter ,020206 networking & telecommunications ,020601 biomedical engineering ,Algorithm ,Brain–computer interface ,Control and Systems Engineering ,Signal Processing ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Computer Vision and Pattern Recognition ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing ,Simulation ,Software - Abstract
International audience; In this paper, the estimation of spatio-temporal patterns in the context of event-related potentials or evoked potentials studies in neuroscience is addressed. The proposed framework (denoted xDAWN) has the advantage to require only the knowledge of the time of stimuli onsets which are determined by the experimental setup. A theoretical analysis of the xDAWN framework shows that it provides asymptotically optimal spatial filters under weak assumptions. The loss in signal to interference-plus-noise ratio due to finite sample effect is calculated in a closed form at the first order of perturbation and is then validated by simulations. This last result shows that the proposed method provides interesting performance and outperforms classical methods, such as independent component analysis, in a wide range of situations. Moreover, the xDAWN algorithm has the property to be robust with respect to the model parameter values. Finally, validations on real electro-encephalographic data confirm the good behavior of the proposed xDAWN framework in the context of a P300 speller brain-computer interface.
- Published
- 2013
33. Rate-Constrained Collaborative Noise Reduction for Wireless Hearing Aids
- Author
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Martin Vetterli and Olivier Roy
- Subjects
Beamforming ,Microphone ,Computer science ,remote source coding with side information ,spatial filtering ,Speech recognition ,Noise reduction ,Monaural ,collaborating hearing aids ,beamforming ,binaural noise reduction ,Background noise ,medicine ,Electronic engineering ,Auditory system ,Wireless ,Active listening ,Electrical and Electronic Engineering ,Digital signal processing ,business.industry ,NCCR-MICS ,NCCR-MICS/CL1 ,medicine.anatomical_structure ,Signal Processing ,wireless link ,business ,Binaural recording - Abstract
Hearing aids are electronic, battery-operated sensing devices which aim at compensating various kinds of hearing impairments. Recent advances in low-power electronics coupled with progresses made in digital signal processing offer the potential for substantial improvements over state-of-the-art systems. Nevertheless, efficient noise reduction in complex listening scenarios remains a challenging task, partly due to the limited number of microphones that can be integrated on such devices. We investigate the noise reduction capability of hearing instruments that may exchange data by means of a rate-constrained wireless link and thus benefit from the signals recorded at both ears of the user. We provide the necessary theoretical results to analyze this collaboration mechanism under two different coding strategies. The first approach takes full benefit of the binaural correlation, while the second neglects it, since binaural statistics are difficult to estimate in a practical setting. The gain achieved by collaborating hearing aids as a function of the communication bit rate is then characterized, both in a monaural and a binaural configuration. The corresponding optimal rate allocation strategies are computed in closed form. While the analytical derivation is limited to a simple acoustic scenario, the latter is shown to capture many of the features of the general problem. In particular, it is observed that the loss incurred by coding schemes which do not consider the binaural correlation is rather negligible in a very noisy environment. Finally, numerical results obtained using real measurements corroborate the potential of our approach in a realistic scenario.
- Published
- 2009
34. Asymptotic Performance Evaluation of Space-Frequency MMSE Filters for OFDM
- Author
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Xavier Mestre and Ana I. Perez-Neira
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Signal processing ,SMI beamformer ,Mean squared error ,Orthogonal frequency-division multiplexing ,spatial filtering ,Filter (signal processing) ,Interference (wave propagation) ,Noise (electronics) ,Sample matrix inversion ,MSINR beamformer ,Signal Processing ,Statistics ,Applied mathematics ,Detection theory ,orthogonal frequency division multiplexing ,Electrical and Electronic Engineering ,Computer Science::Information Theory ,Mathematics - Abstract
This paper proposes and analyzes two different linear space-frequency architectures for the reception of OFDM-modulated signals: the classical sample matrix inversion (SMI) algorithm and a new architecture that maximizes the output signal-to-interference-plus noise ratio (MSINR). The performance of these two linear receivers is compared in terms of asymptotic output SINR, taking into account the finite sample size effect through the asymptotic covariance of the filter weights. The analysis is asymptotic in the sense that the performance is analyzed, assuming that both the number of carriers and the prefix length of the OFDM signal increase without bound at the same rate, whereas their quotient remains constant. Assuming that the carrier frequencies become asymptotically close to one another, we are able to derive explicit equations that shed some light on the influence of the frequency selectivity of channel and interference on the relative performance of the two approaches. The results are useful in the sense that they provide first-order approximations to the (asymptotically) optimum number of adjacent carriers to be processed by a single beamformer in a finite sample size situation.
- Published
- 2004
35. Spatial filtering for pilot-aided WCDMA systems: A semi-blind subspace approach
- Author
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Xavier Mestre and Javier R. Fonollosa
- Subjects
Signal processing ,Spatial filter ,business.industry ,Computer science ,Code division multiple access ,spatial filtering ,pilot-aided CDMA ,Filter (signal processing) ,Multiplexing ,free probability ,Spread spectrum ,WCDMA ,Signal Processing ,Electrical and Electronic Engineering ,Wideband ,Telecommunications ,business ,Algorithm ,Computer Science::Information Theory ,Communication channel - Abstract
This paper proposes a spatial filtering technique for the reception of pilot-aided multirate multicode direct-sequence code division multiple access (DS/CDMA) systems such as wideband CDMA (WCDMA). These systems introduce a code-multiplexed pilot sequence that can be used for the estimation of the filter weights, but the presence of the traffic signal (transmitted at the same time as the pilot sequence) corrupts that estimation and degrades the performance of the,filter significantly. This is caused by the fact that although the traffic and pilot signals are usually designed to be orthogonal, the frequency selectivity of the channel degrades this orthogonality at hte receiving end. Here, we propose a semi-blind technique that eliminates the self-noise caused by the code-multiplexing of the pilot. We derive analytically the asymptotic performance of both the training-only and the semi-blind techniques and compare them with the actual simulated performance. It is shown, both analytically and A. a simulation, that high gains can be achieved with respect to training-only-based techniques.
- Published
- 2003
36. Design strategies for direct multi-scale and multi-orientation feature extraction in the log-polar domain
- Author
-
Fabio Solari, Manuela Chessa, and Silvio P. Sabatini
- Subjects
Foveated images ,Space-variant processing ,Spatial filtering ,Disparity computation ,Design criteria ,Computer science ,Feature extraction ,02 engineering and technology ,01 natural sciences ,law.invention ,Domain (software engineering) ,010309 optics ,Visual processing ,Set (abstract data type) ,Artificial Intelligence ,law ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Cartesian coordinate system ,Computer vision ,Representation (mathematics) ,Spatial filter ,Orientation (computer vision) ,business.industry ,Signal Processing ,020201 artificial intelligence & image processing ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,Algorithm ,Software - Abstract
Despite the well known advantages that a space-variant representation of the visual signal offers, the required adaptation of the algorithms developed in the Cartesian domain, before applying them in the log-polar space, has limited a wide use of such representation in visual processing applications. In this paper, we present a set of original rules for designing a discrete log-polar mapping that allows a direct application in the log-polar domain of the algorithms, based on spatial multi-scale and multi-orientation filtering, originally developed for the Cartesian domain. The advantage of the approach is to gain, without modifications, an effective space-variance and data reduction. Such design strategies are based on a quantitative analysis of the relationships between the spatial filtering and the space-variant representation. We assess the devised rules by using a distributed approach based on a bank of band-pass filters to compute reliable disparity maps, by providing quantitative measures of the computational load and of the accuracy of the computed visual features.
- Published
- 2012
37. Mass Spectrometry Imaging visualization tools developed during the Computis European project
- Author
-
Robbe, Marie-France, Thévenot, Etienne A, Stoeckli, Markus, Hester, Alfons, Roempp, Andreas, Kharchenko, Andriy, Both, Jean-Pierre, Gal, Olivier, Haan, Serge, Laboratoire Outils d'Analyse des Données (LOAD), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Novartis Pharma AG, Justus-Liebig-Universität Gießen = Justus Liebig University (JLU), FOM Institute for Atomic and Molecular Physics (AMOLF), Financial support from the European Commission (FP6 STREP project LSHG-CT-2005-518194), European Project: 32887,COMPUTIS, Robbe, Marie-France, Molecular Imaging in Tissue and Cells by Computer-assisted Innovative Multimode Mass Spectrometry - COMPUTIS - 32887 - OLD, Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), and Justus-Liebig-Universität Gießen (JLU)
- Subjects
Moran index ,[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing ,spatial filtering ,Regions Of Interest ,zooming ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,standardardization ,data interpretation ,mass spectrometry imaging ,spectrum analysis ,peak picking ,molecule identification ,spectrum ,temporal filtering ,statistical analysis ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,peak list ,[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det] ,signal processing ,visualization ,data format ,m/z correlation ,[CHIM.ORGA]Chemical Sciences/Organic chemistry ,[CHIM.ORGA] Chemical Sciences/Organic chemistry ,Magnetic Resonance Imaging ,baseline correction ,image processing ,relative variance ,pixel picking ,classification ,[PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det] ,realignment of images. image coregistration ,spectrum treatment ,data processing ,detrending ,clustering - Abstract
International audience; The Computis European project (2006-2009) was aimed at developing innovative experimental mass spectrometry imaging (MSI) techniques and software tools for data treatment and visualization, and at validating them in key biological applications (neurobiology, pharmaceutical drug development). The project succeeded in defining a specific standard format for MSI, imzML, in collaboration with the HUPO consortium. The four main MSI software tools developed by the project all handle the imzML format.Data Cube Explorer provides an easy spectral and spatial exploration of MS images: spectrum zooming, scrolling through the dataset masses with a manual contrast tuning for images, selection of Regions Of Interest with the display of the associated spectra. The self-organizing map functionality classifies images according to the intensity of all pixel places and automatically selects images as different as possible. Mirion is a simple visualization module displaying spectra by pixel and for the total image, with zooming and scrolling functions. Histogram of the total ion count of each pixel can be calculated, using different input parameters. Images are displayed for each peak of the total spectrum, with a manual intensity tuning and a comparison of the intensity distributions by pixel between several images.EasyMSI enables spatial and spectral visualization of mass spectrometry imaging datasets (spectrum and image display, peak and pixel picking, zooming on spectra and images, ROI selection), as well as an assistance for the interpretation of data: This assistance includes indicators (relative variance, Moran index, m/z correlation) to highlight peaks that bring interesting information, peak list for molecule identification, spectrum denoising or structure analysis by clustering methods (K-means, fuzzy, hierarchical clustering, diffusion map). EasyMSI offers the advantage of processing and displaying the original data (i.e. without binning).BioMap is an image analysis platform for MSI and Magnetic Resonance Imaging. It includes viewing functions (spectrum and image display, intensity adjustment, zoom, treatment of multiple ROIs, geometrical transformations and operations), and spectrum treatment (spatial or temporal filtering, baseline correction, detrending). More elaborated functions enable a simultaneous view of all dataset images, creation of a movie, statistical and histogram analysis, co-registration of images of one or two dataset(s), and realignment of images. The use and capacities of these tools are presented through a comparative analysis of a rodent urinary bladder dataset in imzML format.
- Published
- 2011
38. Ultrasonic Arrays for Sensing and Beamforming of Lamb Waves
- Author
-
Engholm, Marcus
- Subjects
direction of arrival estimation ,dispersive waves ,Lamb waves ,guided waves ,spatial filtering ,imaging ,resonant ultrasound ,Signalbehandling ,Control Engineering ,transducer design ,adaptive beamforming ,array processing ,Reglerteknik ,mode suppression ,Signal Processing ,multi-modal waves - Abstract
Non-destructive testing (NDT) techniques are critical to ensure integrity and safety of engineered structures. Structural health monitoring (SHM) is considered as the next step in the field enabling continuous monitoring of structures. The first part of the thesis concerns NDT and SHM using guided waves in plates, or Lamb waves, to perform imaging of plate structures. The imaging is performed using a fixed active array setup covering a larger area of a plate. Current methods are based on conventional beamforming techniques that do not efficiently exploit the available data from the small arrays used for the purpose. In this thesis an adaptive signal processing approach based on the minimum variance distortionless response (MVDR) method is proposed to mitigate issues related to guided waves, such as dispersion and the presence of multiple propagating modes. Other benefits of the method include a significant increase in resolution. Simulation and experimental results show that the method outperforms current standard processing techniques. The second part of the thesis addresses transducer design issues for resonant ultrasound inspections. Resonant ultrasound methods utilize the shape and frequency of the object's natural modes of vibration to detect anomalies. The method considered in the thesis uses transducers that are acoustically coupled to the inspected structures. Changes in the transducer's electrical impedance are used to detect defects. The sensitivity that can be expected from such a setup is shown to highly depend on the transducer resonance frequency, as well as the working frequency of the instrument. Through simulations and a theoretical argumentation, optimal conditions to achieve high sensitivity are given.
- Published
- 2010
39. Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach
- Author
-
Mestre Pons, Francesc X., Rodríguez Fonollosa, Javier, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, and Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
- Subjects
Signal processing ,Land mobile radio ,Multicode DS/CDMA systems ,Spread spectrum communication ,Channel frequency selectivity ,Multiplexing ,Radio networks ,Processament del senyal ,Self-noise ,Semi-blind techniques ,Beamformers ,Pilot-aided WCDMA systems ,Pilot signals ,Filtering theory ,Semi-blind subspace approach ,Asymptotic performance ,Simulated performance ,Spatial filtering ,Multirate DS/CDMA systems ,Code-multiplexed pilot sequence ,Signal-to-noise-plus -interference ratio ,Code division multiple access ,Traffic signals ,Pilot sequence ,Enginyeria de la telecomunicació::Processament del senyal [Àrees temàtiques de la UPC] ,Telecommunication traffic ,Filter weights estimation ,Broadband networks ,Array signal processing ,Direct-sequence code division multiple access ,Training-only techniques ,Signal detection - Abstract
This paper proposes a spatial filtering technique for the reception of pilot-aided multirate multicode direct-sequence code division multiple access (DS/CDMA) systems such as wideband CDMA (WCDMA). These systems introduce a code-multiplexed pilot sequence that can be used for the estimation of the filter weights, but the presence of the traffic signal (transmitted at the same time as the pilot sequence) corrupts that estimation and degrades the performance of the filter significantly. This is caused by the fact that although the traffic and pilot signals are usually designed to be orthogonal, the frequency selectivity of the channel degrades this orthogonality at hte receiving end. Here, we propose a semi-blind technique that eliminates the self-noise caused by the code-multiplexing of the pilot. We derive analytically the asymptotic performance of both the training-only and the semi-blind techniques and compare them with the actual simulated performance. It is shown, both analytically and via simulation, that high gains can be achieved with respect to training-onlybased techniques.
- Published
- 2003
40. Command of a Virtual Neuroprosthesis-Arm with Noninvasive Field Potentials
- Author
-
Foldes, Stephen Thomas
- Subjects
- Biomedical Engineering, Neurosciences, Rehabilitation, Brain Machine Interfacing, Brain Computer Interfacing, Electroencephalography, Functional Electrical Stimulation, Neuroprosthesis, Spatial Filtering, Rehabilitation Engineering, Neural Engineering, Signal Processing
- Abstract
Assistive devices, such as motor neuroprostheses, have been developed to help restore function for individuals with tetraplegia. For individuals with severe paralysis, command sources for assistive devices are limited to muscle activity and/or movements of the head and face. These commands can impede eating, talking, and other activities. Incorporating signals from the brain may be a valuable way to augment the command options for complex devices.The attempted movements of body parts generate characteristic changes in field potentials over brain areas associated with those body parts. These movement-related changes can be recorded from the scalp and used to control an assistive device. Most previous studies using movement-related field potentials as a command source have been focused on the abstract control of computer cursors and not specifically focused on restoring arm and hand function using neuroprostheses.We developed new spatial filtering techniques to help separate the cortical activities associated with the movement and rest of different body parts. Using these novel spatial filters, we demonstrated that two-dimensional movement of a ‘virtual upper-extremity neuroprosthesis’ can be controlled using electroencephalography (EEG) signals that are modulated by the attempted movement of two body parts which are spread apart in the motor homunculus (i.e. hand and feet). The attempted movement of the feet and hand was an abstract command strategy using body parts unrelated to the desired device movement. A more natural command strategy of using the attempted movements of arm and hand joints was evaluated as a more intuitive way to control the same joints of the neuroprosthesis. Using a more natural command strategy, we demonstrated that individuals with tetraplegia were able to intuitively control the grasp of a virtual hand using movement-related field potentials associated with hand extension and relaxation. When expanding intuitive control to combinations of the elbow, shoulder, and hand together, our offline analysis showed a reduction in decoding accuracy over abstract command strategies in able-bodied individuals but equivalent or improved accuracy in the tetraplegic participants. Demonstrating real-time control of a virtual upper-limb neuroprosthesis using EEGs is an important step towards the clinical implementation of brain-controlled motor neuroprostheses.
- Published
- 2010
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