Search

This study addresses the comparison of the deoxyribonucleic acid (DNA) of six primates in the perspective of fractals and signal processing. The species consist of Bonobo, Chimpanzee, Gorilla, Human, Orangutan, and Rhesus macaque. These primates are very close in the life evolution and, therefore, pose a problem for designing assertive algorithms to detect their phylogenetic tree. The paper associates logical and mathematical concepts inspired in signal processing and dynamical systems for the analysis of the DNA data of the chromosomes. The results are compared by means of computer visualization tools. [ABSTRACT FROM AUTHOR]

The paper deals with shear stresses analysis of fully saturated Nevada sand layer by means of Wavelet Transform. The layer modelled as two-phase Biot΄s porous medium, is subjected to the impulse wave. Results, obtained from program called Swandyne, were analyzed using MathCad. The Wavelet Transform was carried out to calculate proper frequency spectrum along with duration time of separate frequency. Tangential stresses were considered because of they importance in creating slip plane and liquefaction. In order to study the dynamic response of saturated soil layer as an initial-boundary problem, a FEM code was implemented. The tangential stress distribution in the layer for chosen time steps shows that the phenomena well known under static load takes place during dynamic excitation as well. The shear stresses in the reference point, are analysed using two methods, classical Fourier Transform and the modern Wavelet Analysis. Thanks to Wavelet Transform we can retrieve such important information as: the time when the dominant frequency is reached and which frequencies appears and/or disappears in time. [ABSTRACT FROM AUTHOR]

Detection of an incipient internal defect from a measurement point on the surface of a machine is often made difficult due to the corruption of the source signal by background noise usually through the transmission path. In order to detect or recover the source signal, it is essential to suppress or remove this background noise. With the advancement of digital signal processing techniques, this removal can be achieved using fixed or adaptive filters. The main problem with the application of filtering techniques is that one has to know the characteristics of the noise in advance or may require more than two channels of data if using an adaptive filter. This paper reports on the application of Blind Deconvolution method to recover fault information from the measured (observed) signals of a damaged bearing through the transmission channel and which was also corrupted by noise.. The Blind Deconvolution method manages to recover the fault signal by estimating the inverse of the transmission (channel transfer function) path using the eigenvector algorithm (EVA). Modified crest factor (MCF) and Arithmetic Mean (AM) algorithms were used to optimise the equalizer parameters. Computer simulation and experimental studies were used to verify the applicability of the technique. [ABSTRACT FROM AUTHOR]

In this paper, we propose an aperiodic stochastic resonance (ASR) signal processor for communication systems based on a bi-stable mechanism. This processor can detect base-band binary pulse amplitude modulation (PAM) signals. In this processor related parameters can be adjusted. The adjustment mechanism is explained from the perspective of the conventional noise-induced nonlinear signal processing. To demonstrate this processors usability, based on it we implemented a digital image watermarking algorithm in the discrete cosine transform (DCT) domain. In this algorithm, the watermark and the DCT alternating current (ac) coefficients of the image are viewed as the input signal and the channel noise, respectively. This phenomenon that the detection bit error ratio (BER) of the system suffering from certain attacks is lower than that of the system not suffering from any attack is systematically analyzed. [ABSTRACT FROM AUTHOR]

This paper addresses the formalization in higher-order logic of fixed-point arithmetic based on the SPW (Signal Processing WorkSystem) tool. We encoded the fixed-point number system and specified the different rounding modes in fixed-point arithmetic such as the directed and even rounding modes. We also considered the formalization of exceptions detection and their handling like overflow and invalid operation. An error analysis is then performed to check the correctness of the rounding and to verify the basic arithmetic operations, addition, subtraction, multiplication and division against their mathematical counterparts. Finally, we showed by an example how this formalization can be used to enable the verification of the transition from the floating-point to fixed-point algorithmic levels in the design flow of signal processors. [ABSTRACT FROM AUTHOR]

Vibration signals are important state parameters for mechanical equipments΄ status monitoring and fault diagnosis. In this paper, in order to overcome the limitations of the traditional vibration measurement med1ods and instrument, a new non-contacting vibration method based on ultrasonic for vibration detection in special environment was presented. The mainly researched in this paper were the circuit for ultrasonic transmitting, receiving, algorithm and the module based on LabVIEW for signal analysis and processing. New algorithm was adopted in the system design. The measurement for vibration signals, which may have higher accuracy, was based on ultrasonic wave of different frequency. Experiments were carried on for proving the theory and the result was expected, verifying the reliability and feasibility of the system. [ABSTRACT FROM AUTHOR]

In this paper, we propose a ˵Spatial speaker″, an enhancement of a Java FreeTTS speech synthesizer with the additional function of spatial positioning of both the speaker and the listener. Our module enables the reading of an arbitrary text from a file or webpage to the user from a fixed or changing position in space through normal stereo headphones. Our solution combines the following modules: FreeTTS speech synthesizer, a custom made speech processing unit, MIT Media Lab HRTF library, JOAL positioning library and Creative X-Fi sound card. The paper gives an overview of the design of the ˵Spatial Speaker″ and proposes three different practical applications of such a system for visually impaired and blind computer users. Some preliminary results of user studies confirmed the system΄s usability and showed its great potential also in other types of applications and auditory interfaces. The entire system is developed as a single Java class which can be imported and used in any Java application. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of EEG signal processing methods for studying correlations between human muscle and brain activity. The main task of this work is to design the methods of EEG signal processing and to verify them on artificial and real signals. The paper introduces methods of EEG processing in time and frequency domain. [ABSTRACT FROM AUTHOR]

This paper presents an alternative energy-based algorithm to provide speech/silence classification. The algorithm is capable to track non-stationary signals and dynamically calculate instantaneous value for threshold using adaptive scaling parameter. It is based on the observation of a noise power estimation used for computation of the threshold can be obtained using minimum and maximum values of a short-term energy estimate. The paper presents this novel voice activity detection algorithm, its performance, its limitations, and some other techniques which deal with energy estimation as well. [ABSTRACT FROM AUTHOR]

A filter is a device that passes electric signals at certain frequency or frequency ranges while preventing the passage of others. This paper focuses on active low-pass Butterworth filters design. In communication, data acquisition system usually requires anti-aliasing low-pass filter as well as low-pass noise filter in their preceding signal condition stages. In this paper design of fourth-order low-pass filters is the main topic of consideration. This paper will examine how to implement Butterworth filter and design methods. And this paper describes mathematics calculations and implementation of Butterworth filter with MATLAB and Circuit Maker. [ABSTRACT FROM AUTHOR]

The quasientropy (QE) is a class of infinitely many functions of probabilities that is similar to the Shannon entropy. In this paper, we review the application of the QE approach to independent component analysis (ICA) and chaotic time series analysis. We also report the new progress of the QE approach to textural features extraction in image processing. [ABSTRACT FROM AUTHOR]

An array antenna system with innovative signal processing can enhance the resolution of a signal direction of arrival (DOA) estimation. Super resolution algorithms take advantage of array antenna structures to better process the incoming signals. They also have the ability to identify multiple targets. This paper explores the eigen-analysis category of super resolution algorithm. A class of Multiple Signal Classification (MUSIC) algorithms known as a root-MUSIC algorithm is presented in this paper. The root-MUSIC method is based on the eigenvectors of the sensor array correlation matrix. It obtains the signal estimation by examining the roots of the spectrum polynomial. The peaks in the spectrum space correspond to the roots of the polynomial lying close to the unit circle. Statistical analysis of the performance of the processing algorithm and processing resource requirements are discussed in this paper. Extensive computer simulations are used to show the performance of the algorithms. [ABSTRACT FROM AUTHOR]

Frequency domain adaptive filters are attractive in applications requiring a large number of coefficients such as acoustic echo cancellation (AEC). Our recent paper derived a not-so-restrictive fixed common step-size bound for the generalized multidelay adaptive filter (GMDF). Based on this bound, this paper introduces a new frequency-domain regularization for the GMDF algorithm. Extensive simulation results demonstrate the usefulness of our algorithm in the scenario of speech input signals. [ABSTRACT FROM AUTHOR]

An array antenna system with innovative signal processing can enhance the resolution of a signal direction of arrival (DOA) estimation. Super resolution algorithms take advantage of array antenna structures to better process the incoming signals. They also have the ability to identify multiple targets. This paper explores the Polynomial Roots Intersection for Multi-dimensional Estimation (PRIME) algorithms. The PRIME algorithm allows a polynomial rooting approach to estimate joint azimuth/elevation parameters of the signal detection for planer arrays. This method calculates a finite set of root intersections, which are the simultaneous solutions from multiple independent multivariate polynomials. The solutions for the source angle information are included in the simultaneous solutions. The PRIME algorithm does not require the use of a scan vector to scan all possible directions. The results demonstrate improvement in both resolution and computational efficiency with no loss of accuracy. Statistical analysis of the performance of the processing algorithm and processing resource requirements are discussed in this paper. Extensive computer simulations are used to show the performance of the algorithms. [ABSTRACT FROM AUTHOR]

Case-based reasoning (CBR) solves problems using the already stored knowledge, and captures new knowledge, making it immediately available for solving the next problem. Therefore, CBR can be seen as a method for problem solving, and also as a method to capture new experience and make it immediately available for problem solving. The CBR paradigm has been originally introduced by the cognitive science community. The CBR community aims to develop computer models that follow this cognitive process. Up to now many successful computer systems have been established on the CBR paradigm for a wide range of real-world problems. We will review in this paper the CBR process and the main topics within the CBR work. Hereby we try bridging between the concepts developed within the CBR community and the statistics community. The CBR topics we describe are: similarity, memory organization, CBR learning, and case-base maintenance. Then we will review based on applications the open problems that need to be solved. The applications we are focusing on are meta-learning for parameter selection, image interpretation, incremental prototype-based classification and novelty detection and handling. Finally, we summarize our concept on CBR. [ABSTRACT FROM AUTHOR]

One of recent advances in biotechnology offers high-throughput mass-spectrometry data for disease detection, prevention, and biomarker discovery. In fact proteomics has recently become an attractive topic of research in biomedicine. Signal processing and pattern classification techniques are inherently essential for analyzing proteomic data. In this paper the estimation method of block kriging is utilized to derive an error matching strategy for classifying proteomic signals with a particular application to the prediction of cardiovascular events using clinical mass spectrometry data. The proposed block kriging based classification technique has been found to be superior to other recently developed methods. [ABSTRACT FROM AUTHOR]

This paper aims at investigating methods for features extraction for emotions recognition of a speech signal. The paper discusses the possible methodologies for the features as acoustic, lexical, and discourse features, and classification algorithms for classifying spoken utterances based on the emotional state of the speaker [1]. Besides applications in enabling natural human machine interfaces, the paper motivates development of novel method of applying feature extraction and classification techniques that can operate with speech data. [ABSTRACT FROM AUTHOR]

MIMO radar (Multiple input multiple output radar) is a new radar developed recently. It outperforms the conventional phased radar in target detection. In this paper, the non-ideal factor of transmitting signal is considered. Firstly, the signal model of MIMO radar is investigated. And then the steps of the signal processing in MIMO radar are researched. At last, a simulation platform is established with the MATLAB to testify the advantage of MIMO radar over its conventional counterpart. [ABSTRACT FROM AUTHOR]

This paper presents the initial results of a research project that aims to develop a method for losses/leakage detection and household water consumption characterization through the detailed patterns analysis of signals generated by water meters. The Department of Civil Engineering (University of Coimbra) supports the research as part of a PhD Project. An experimental facility is used for signals acquisition and data analysis will be performed by using a pattern recognition algorithm that will identify the hydraulic devices in use. It is intended to develop and test some algorithm structures at various plumbing configuration forms to find the best one. In a second phase, a consumption analysis will be carried out using that algorithm to test its efficiency in inhabited houses. The expectation is to develop an efficient water monitoring tool that helps the users to follow-up and to control the water consumption using a computer or even a mobile device. [ABSTRACT FROM AUTHOR]

A constant aspiration to optimize electric arc steelmaking process causes an increase of the use of advanced analytical methods for the process support. Optimization of the production processes lead to real benefits, which are, for example, lower costs of production. More often computational intelligence methods are used for this purpose. In this paper authors present three methods used for identification of liquid state of scrap in electric arc furnace using analysis of signals of the current of furnace electrodes. [ABSTRACT FROM AUTHOR]

The paper presents preliminary results of data analysis and discusses the application of soft computing methods in the field of non-destructive tests. The main objective of developed diagnostic system are the automatic detection and evaluation of damage. Thus the system is composed of two signal processing techniques known as novelty detection and pattern recognition. For this purpose autoassociative as well as feed-forward neural networks are used. All the signals used for training the system are obtained from laboratory tests of strip specimens, where phenomenon of elastic wave propagation in solids was utilized. Computed parameters of time signals defines various types of input vectors used for training neural networks. The results finally obtained prove that the proposed diagnostic system made automation of structure testing possible and can be applied to Structural Health Monitoring. [ABSTRACT FROM AUTHOR]

In order to apply the Extended Alternating Projection Neural Network (EAPNN) better in pattern recognition, signal processing and sensor network, the paper makes futher research on the EAPNN and deduces several important conclusions from the mathematical expression to the steady state value of EAPNN, and strict mathematical proofs to these corollaries are also given. In addition, the convergent speed of EAPNN has been discussed and analyzed. [ABSTRACT FROM AUTHOR]

This paper presents a new algorithm for the determination of the Autoregressive Moving Average (ARMA) model order based on Artificial Neural Network (ANN). The basic idea is to apply ANN to a special matrix constructed from the Minimum Eginevalue (MEV) criterion. The MEV criterion is based on a covariance matrix derived from the observed output data only. The input signal is unobservable. The proposed algorithm is based on training the MEV covariance matrix dataset using the back-propagation technique. Our goal is to develop a system based on ANN; hence, the model order can be selected automatically without the need of prior knowledge about the model or any human intervention. Examples are given to illustrate the significant improvement results. [ABSTRACT FROM AUTHOR]

The continued advancement of software-defined radio (SDR) technology has been a key factor in furthering research about the implementation of most signal processing algorithms at baseband. Traditionally, most algorithms have been carried out at radio frequency (RF). With the coming of SDR, the processing can be done at baseband frequencies which are more compatible with the fast developing software radio technology. This paper looks at matched filter detection and investigates the possibility and benefits of carrying out the detection process at quadrature baseband (QBB). A simple chirp signal is considered for the analysis. The analysis is carried out using MatLab simulations at RF and QBB and the results do show the possibility of carrying out the detection process at QBB with the expected benefits as compared to carrying out the process at RF. [ABSTRACT FROM AUTHOR]

Electro-optical system that combines the advantages of optical and electronic system has been widely applied in signal processing. Because of advantages of real-time, parallel operation capability, and programmable flexibility, it is especially utilized in the pattern recognition, e.g., military radar system, secure entry system, biomedical detection, and many other applications. Moreover, color is one of the most significant and powerful visual information. Improving the JTC for polychromatic pattern recognition is a novel topic. Deutsch proposed a multi-channel single-output JTC. It is based on RGB color model and separates the color pattern into red, green, and blue components respectively and then displays on the spatial light modulator (SLM). Thereafter, RGB become a popular model to perform pattern recognition. However, it is known that red, green, and blue components are correlated with one another. Furthermore, there are some cases in which the use of the RGB chromatic system is not appropriate for obtaining effective polychromatic object recognition, e.g., RGB decomposition is not appropriated for discriminating between similar color objects. Therefore, we propose a novel nonzero order JTC based on ATD color model to achieve polychromatic pattern recognition. ATD color model is constituted by achromatic, tritanopic, and deuteranopic systems. People consider that ATD color model is the most to be close to human eyes. In this paper, we apply ATD color model to multi-channel nonzero order joint transform correlator and perform pattern recognition. To estimate whether ATD color model is suitable for pattern recognition, we compare with RGB, which is common used to perform pattern recognition. The terms of estimation contain recognition ability of rotational distortion, brightness performance, multi-level quantized reference functions, noise tolerance ability, and relationship between channels and channels. We utilize peak to correlation energy, peak to sidelobe ratio, correlation peak intensity, and mutual correlation coefficient as our performance evaluation parameters. Finally, the results show that ATD color model is suitable for pattern recognition. [ABSTRACT FROM AUTHOR]

The continued advancement of software-defined radio (SDR) technology has been a key factor furthering research into the implementation of most signal processing algorithms at baseband. Traditionally, most algorithms have been carried out at radio frequency (RF). With the coming of SDR, the processing can be done at baseband frequencies which are more compatible with the fast developing software radio technology. This paper looks at selected demodulation algorithms and investigates the possibility and benefits of carrying them out at quadrature baseband (QBB). Simple beamforming, multipath/Doppler shift compensation cases are considered. The analysis is carried out using MatLab simulations at RF and QBB and the results do show the possibility of carrying out the selected demodulation algorithms at QBB with the expected benefits. [ABSTRACT FROM AUTHOR]

In recent years wireless mesh network (WMN) technologies and their applications have been actively researched and developed as the promising solution for future wireless mobile networks. Conversely security of WMN is often a secondary reflection in development. In our previous work we proposed Artificial Immune System model to employ in secure routing in WMN. This paper proposes an emerging perception to model danger signal exchange between nodes in WMN by emulating the function of Cytokines in Human Immune System (HIS). [ABSTRACT FROM AUTHOR]

Frequency hopping spread spectrum (FHSS) has been paid much attention and has been employed by various wireless systems. For the reception of FHSS signals, first of all, we need to detect the presence of signal, and then to estimate hop parameters such as hop timing and hop frequency. In this paper, we propose an efficient algorithm for joint detection and hop parameters estimation of the slow FHSS/MFSK signals using two different methods, namely, the Discrete Haar Wavelet Transform (DHWT) and the autocorrelation (AC) in Rayleigh block fading channels. This algorithm can be used in communication intelligent (COMINT) systems for surveillance issues. The performance and behavior of the proposed algorithm are examined through computer simulations over practical measured data. [ABSTRACT FROM AUTHOR]

Joint approximate diagonalization is one of well-known methods for solving independent component analysis and blind source separation. It calculates an orthonormal separating matrix which diagonalizes many cumulant matrices of given observed signals as accurately as possible. It has been known that such diagonalization can be carried out efficiently by the Jacobi method, where the optimization for each pair of signals is repeated until the convergence of the whole separating matrix. The Jacobi method decides whether the optimization is actually applied to a given pair by a convergence decision condition. Generally, a fixed threshold is used as the condition. Though a sufficiently small threshold is desirable for the accuracy of results, the speed of convergence is quite slow if the threshold is too small. In this paper, we propose a new decision condition with an adaptive threshold for joint approximate diagonalization. The condition is theoretically derived by a model selection approach to a simple generative model of cumulants in the similar way as in Akaike information criterion. In consequence, the adaptive threshold is given as the current average of all the cumulants. Only if the expected reduction of the cumulants on each pair is larger than the adaptive threshold, the pair is actually optimized. Numerical results verify that the method can choose a suitable threshold for artificial data and image separation. [ABSTRACT FROM AUTHOR]

In this paper, a minimum variance estimator for the gain nonuniformity (NU) in infrared (IR) focal plane array (FPA) imaging system is presented. Recently, we have developed a recursive filter estimator for the offset NU using only the collected scene data, assuming that the offset is a constant in a block of frames where it is estimated. The principal assumption of this scene-based NU correction (NUC) method is that the gain NU is a known constant and does not vary in time. However, in several FPA real systems the gain NU drift is significant. For this reason, in this work we present a gain NU drift estimation based on the offset NU recursive estimation assuming that gain and offset are jointly distributed. The efficacy of this NUC technique is demonstrated by employing several real infrared video se quences. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a method which uses a note model and signal post processing for a musical instrument to make a piece of music. one of the important issues in note transcription is extraction of multiple pitches. Most of the examined methods face error in joint harmonics and frequencies. A good model for note of a specified musical instrument can help us identify a note better. The presented method is based on wavelet transform, onset detection, note model and conformity reduction error algorithm or regression and post-processing for improved result. The results obtained show that detecting musical notes in a piece played on the guitar is, in comparison with similar methods, of higher detection accuracy and even in the case of noisy sound signals, the results are more acceptable. [ABSTRACT FROM AUTHOR]

In the paper, the estimation algorithm of eye blinking for a computer animation system using biopotentials occurring on an actor΄s face is considered. The measuring system incorporates minimal 3–electrodes configuration, which is relatively cheap solution. The proposed algorithm allows both the measurement of eyes orientation and detection of eyes blinking. [ABSTRACT FROM AUTHOR]

In this paper, the coexistence of WiMAX system and existing fixed wireless access (FWA) systems is studied. Spectral emission mask is used as well as interference to noise ratio (I/N) of -6 dB as one of standard sharing criterion value at FWA systems recommended by international telecommunication union radio sector ITU-R. Three channel bandwidths of (3.5, 7, and 10 MHz) of WiMAX system are selected to be studied with 7 MHz FWA channel in dense urban area. All parameters of the two systems are presented and methodology is explained. It is well known that frequency distance rules are an important of frequency coordination process in most radio services, so frequency and distance separations are determined and analyzed for both terms cochannel interference and adjacent channel interference in the different interference scenarios which are supposed. [ABSTRACT FROM AUTHOR]