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Sparse component analysis techniques have been successfully applied to the separation of speech sources. This paper presents an efficient algorithm based on the matching pursuit approach to deal with multichannel records. The proposed algorithm explicitly employs spatial constraints among different channels to express mixed signals as linear combinations of delayed components selected from an overcomplete dictionary. We present a new procedure for estimating the mixing system parameters (attenuations and delays), which can be applied to more than two mixtures and is not restricted to non-negative attenuation coefficients. The proposed mixing system estimation method can accommodate delays of greater magnitude than traditional approaches. In addition, learned dictionaries that improve the identification step can be used when excerpts from sources (exogenous to mixtures) are available. The simulation results show that semi-blind dictionaries perform better than those used in blind configurations. [ABSTRACT FROM AUTHOR]

In this paper, we propose an improved atmospheric scattering model (IASM) to overcome the inherent limitation of the traditional atmospheric scattering model. Based on the IASM, a fast single image dehazing algorithm is also presented. In this algorithm, by constructing a linear model between the transmission and the haze aware density feature, the transmission map can be directly estimated through a linear operation on three components: luminance, saturation and gradient. Combining the sky-relevant feature and the proposed guided energy model (GEM), we can accurately estimate the atmospheric light and scene incident light, and can further restore the scene albedo via the IASM. Finally, an accelerating framework (AF) based on the Gaussian–Laplacian pyramid is proposed to increase the computational speed. Experimental results demonstrate that the proposed algorithm outperforms most of the prevalent algorithms in terms of visual effect and computational efficiency. Besides, it is also capable of processing various types of degraded images in addition to hazy images. [ABSTRACT FROM AUTHOR]

In this paper we consider the problem of reconstructing sources in a homogeneous viscoelastic medium from wavefield measurements. We first present a modified time-reversal imaging algorithm based on a weighted Helmholtz decomposition and justify mathematically that it provides a better approximation than by simply time reversing the displacement field, where artifacts appear due to the coupling between the pressure and shear waves. Then we investigate the source inverse problem in an elastic attenuating medium. We provide a regularized time-reversal imaging which corrects the attenuation effect at the first order. The results of this paper yield the fundamental tools for solving imaging problems in elastic media using cross-correlation techniques. [ABSTRACT FROM PUBLISHER]

Nonlocal means filtering is a noise attenuation method based on redundancies in image information. It is also a nonlocal denoising method that uses the self-similarity of an image, assuming that the valid structures of the image have a certain degree of repeatability that the random noise lacks. In this paper, we use nonlocal means filtering in seismic random noise suppression. To overcome the problems caused by expensive computational costs and improper filter parameters, this paper proposes a block-wise implementation of the nonlocal means method with adaptive filter parameter estimation. Tests with synthetic data and real 2D post-stack seismic data demonstrate that the proposed algorithm better preserves valid seismic information and has a higher accuracy when compared with traditional seismic denoising methods (e.g., f-x deconvolution), which is important for subsequent seismic processing and interpretation. [ABSTRACT FROM AUTHOR]

Abstract: The paper concerns active control of impulsive noise having peaky distribution with heavy tail. Such impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The most famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems is based on the minimization of variance (second order moment) of error signal, and hence, becomes unstable for the impulsive noise. In order to improve the robustness of adaptive algorithms for processes having distributions with heavy tails (i.e. signals with outliers), either (1) a robust optimization criterion may be used to derive the adaptive algorithm or (2) the large amplitude samples may be ignored or replaced by an appropriate threshold value. Among the existing algorithms for ANC of impulsive noise, one is based on the minimizing least mean p-power (LMP) of the error signal, resulting in FxLMP algorithm (approach 1). The other is based on modifying; on the basis of statistical properties; the reference signal in the update equation of the FxLMS algorithm (approach 2). In this paper we propose two solutions to improve the robustness of the FxLMP algorithm. In first proposed algorithm, the reference and the error signals are thresholded before being used in the update equation of FxLMP algorithm. As another solution to improve the performance of FxLMP algorithm, a modified normalized step size is proposed. The computer simulations are carried out, which demonstrate the effectiveness of the proposed algorithms. [Copyright &y& Elsevier]

Dual-energy computed tomography (DECT) allows one to obtain both density and atomic number and thus can provide information about material composition of scanned objects. In this paper, we extend a basis material decomposition method for high energy X-ray DECT used in cargo inspection. It differs from conventional DECT reconstruction methods by pair-production effect coming into play in the reconstruction. The pair-production does not happen for DECT in low energy level (lower than 1 MeV). The decomposition error of the basis material model and its applicability in the high-energy level are analyzed in this paper. A reconstruction method based on this model is proposed to reconstruct both the atomic number Z and the electron density \rhoe images for a high-energy DECT. The method is validated by a numerical simulation and a practical experiment on a cargo inspection system. Results show that the proposed reconstruction method is strongly grounded on physics and feasible for high-energy DECT in material discrimination, especially for cargo inspections. The advantages and limitations of the high-energy DECT, as well as possible improvements for future work are discussed in this paper. [ABSTRACT FROM AUTHOR]

Monitoring of precipitation using higher-frequency radar systems such as X band is becoming popular. At X-band frequency, weather radar signals are attenuated along their paths due to precipitation. A network-based reflectivity retrieval technique has been developed for the Collaborative Adaptive Sensing of the Atmosphere (CASA) system, which is a radar network that can observe a weather event simultaneously by multiple radars. This paper describes the design and implementation of an architectural framework for real-time processing of the network-based attenuation correction system. The benchmarks presented here show that the system accomplishes networked attenuation correction within a few seconds, making it well suited for the CASA system. This paper presents the performance of the network-based attenuation correction system in terms of the metrics of attenuation correction as well as computational performance using CASA Integrated Project 1 (IP1) data during 2007--09 field experiments. The results show that the network-based attenuation correction algorithm works robustly in real time while retrieving attenuation-corrected reflectivity. [ABSTRACT FROM AUTHOR]

A filter design using insertion loss method (ILM) and Particle Swarm Optimization algorithm (PSO) is presented in the paper. ILM is generally a preferred technique for the filter design with an arbitrary number of elements. This method can be used to create the filter which has different types of frequency responses. However, this procedure is not practical for a large number of elements. PSO algorithm can be a useful procedure for calculating values in filters with a large number of elements. This paper presents the procedure which takes an advantage of ILM for filter design and PSO for determination an unknown component values in filters with large number of elements. This is suitable approach for filter design with an arbitrary cutoff frequency and shape of pass band. [ABSTRACT FROM AUTHOR]

Abstract  This paper shows a promising method for acoustic barrier design using a new acoustic material called Sonic Crystals (SCs). The configuration of these SCs is set as a multiobjective optimization problem which is very difficult to solve with conventional optimization techniques. The paper presents a new parallel implementation of a Multiobjective Evolutionary Algorithm called ev-MOGA (also known as ) and its application in a complex design problem. ev-MOGA algorithm has been designed to converge towards a reduced, but well distributed, representation of the Pareto Front (solution of the multiobjective optimization problem). The algorithm is presented in detail and its most important properties are discussed. To reduce the ev-MOGA computational cost when objective functions are substantial, a basic parallelization has been implemented on a distributed platform. [ABSTRACT FROM AUTHOR]

High Altitude Platforms (HAPs) are currently experiencing a great interest as potential solutions for the growing demand of wireless broadband applications, but their rapid motion and the characteristics of the stratospheric channel, which may cause strong attenuation, multipath fading and Doppler shift, can strongly impact their performances. The described scenario requires the use of beamforming techniques, able to provide medium to high gains in a mobile environment. Given these premises, this paper discusses the conjugation of OFDM techniques with smart antennas for HAP-based communications, stressing the need for integration of the different functional blocks of an OFDM receiver. In fact, in order to face a time varying scenario, adaptive techniques are needed, and only a careful joint design of time and frequency synchronization with beamforming algorithms can guarantee reliable communication. The detailed and integrated receiver design described in the paper is based on the OFDM version of the IEEE 802.16a transmission standard. [ABSTRACT FROM AUTHOR]

In this paper, both the asymptotic stability and l ∞ persistent disturbance attenuation issues are investigated for a class of networked control systems (NCSs) under bounded uncertain access delay and packet dropout effects. The basic idea is to formulate such NCSs as discrete-time switched systems with arbitrary switching. Then the NCSs' stability and performance problems can be reduced to the corresponding problems of such switched systems. The asymptotic stability problem is considered first, and a necessary and sufficient condition is derived for the NCSs' asymptotic stability based on robust stability techniques. Secondly, the NCSs' l ∞ persistent disturbance attenuation properties are studied and an algorithm is introduced to calculate the l ∞ induced gain of the NCSs. The decidability issue of the algorithm is also discussed. A network controlled integrator system is used throughout the paper for illustration. [ABSTRACT FROM AUTHOR]

Path planning is critical to the efficiency and fidelity of robot navigation. The solution of robot path planning is to seek a collision-free and the shortest path from the start node to target node. In this paper, we propose a new improved artificial fish swarm algorithm (IAFSA) to process the mobile robot path planning problem in a real environment. In IAFSA, an attenuation function is introduced to improve the visual of standard AFSA and get the balance of global search and local search; also, an adaptive operator is introduced to enhance the adaptive ability of step. Besides, a concept of inertia weight factor is proposed in IAFSA inspired by PSO intelligence algorithm to improve the convergence rate and accuracy of IAFSA. Five unconstrained optimization test functions are given to illustrate the strong searching ability and ideal convergence of IAFSA. Finally, the ROS (robot operation system) based experiment is carried out on a Pioneer 3-DX mobile robot; the experiment results also show the superiority of IAFSA. [ABSTRACT FROM AUTHOR]

In many classes of applications like active vibration control and active noise control, the disturbances can be characterized by their frequency content and their location in a specific region in the frequency domain. The disturbances can be of narrow band type (simple or multiple) or of broad band type. A model can be associated to these disturbances. The knowledge of this model allows to design an appropriate control system in order to attenuate (or to reject) their effect upon the system to be controlled. The attenuation of disturbances by feedback is limited by the Bode Integral and the 'water bed' effect upon the output sensitivity function. In such situations, the feedback approach has to be complemented by a 'feedforward disturbance compensation' requiring an additional transducer for obtaining information upon the disturbance. Unfortunately, in most of the situations, the disturbances are unknown and time-varying and therefore an adaptive approach should be considered. The generic term for adaptive attenuation of unknown and time-varying disturbances is 'adaptive regulation' (known plant model, unknown, and time-varying disturbance model). The paper will review a number of recent developments for adaptive feedback compensation of multiple unknown and time-varying narrow band disturbances and for adaptive feedforward compensation of broad band disturbances in the presence of the inherent internal positive feedback caused by the coupling between the compensator system and the measurement of the image of the disturbance. Some experimental results obtained on a relevant active vibration control system will illustrate the performance of the various algorithms presented. Some open research problems will be mentioned in the conclusion. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A variational algorithm for estimating measurement error covariance and the attenuation of X-band polarimetric radar measurements is described. It concurrently uses both the differential reflectivity ZDR and propagation phase ΦDP. The majority of the current attenuation estimation techniques use only ΦDP. A few of the ΦDP-based methods use ZDR as a constraint for verifying estimated attenuation. In this paper, a detailed observing system simulation experiment was used for evaluating the performance of the variational algorithm. The results were compared with a single-coefficient ΦDP-based method. Retrieved attenuation from the variational method is more accurate than the results from a single coefficient ΦDP-based method. Moreover, the variational method is less sensitive to measurement noise in radar observations. The variational method requires an accurate description of error covariance matrices. Relative weights between measurements and background values (i.e., mean value based on long-term DSD measurements in the variational method) are determined by their respective error covariances. Instead of using ad hoc values, error covariance matrices of background and radar measurement are statistically estimated and their spatial characteristics are studied. The estimated error covariance shows higher values in convective regions than in stratiform regions, as expected. The practical utility of the variational attenuation correction method is demonstrated using radar field measurements from the Taiwan Experimental Atmospheric Mobile-Radar (TEAM-R) during 2008's Southwest Monsoon Experiment/Terrain-Influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX). The accuracy of attenuation-corrected X-band radar measurements is evaluated by comparing them with collocated S-band radar measurements. [ABSTRACT FROM AUTHOR]

Carbon fibre-reinforced polymer (CFRP) composites are increasingly used in safety and infrastructure-critical applications in the aerospace and renewable energy industries. However, such material poses a significant challenge to the ultrasonic non-destructive testing process due to its high attenuation, inhomogeneous structure and anisotropic acoustic properties. Current methods are limited to the implementation of inspection using ultrasonic beams normal to the surface. This is due to the velocity varying angularly within composites, which leads to unpredictable inspection results when using oblique beams. This paper describes two methods used to determine the measurement of velocity variations present in CFRP components with the aim of providing a velocity profile applied to the full matrix capture (FMC) imaging algorithm. From these measurements, a modified version of the total- focusing method (TFM) algorithm is provided, which allows for velocity changes in relation to the angle to be considered. Experimental results are then presented, indicating successful incorporation of the velocity profile where fully- focused imagery of several side-drilled holes was generated from a CFRP component. [ABSTRACT FROM AUTHOR]

Microultrasound (micro-US), also known as ultrasound biomicroscope, is able to delineate small structures with fine spatial resolution. However, micro-US suffers limited depth of penetration due to significantly large attenuation at high frequencies. Modulated excitation imaging has displayed the capability to improve the penetration depth, while maintaining the spatial resolution. But the effectiveness of this technique in micro-US has not been fully demonstrated. In addition, the current modulated excitation imaging systems for micro-US are designed for specific excitation method, therefore, lack of flexibility, and are typically bulky and expensive. This paper presents the development of a novel system to achieve modulated excitation imaging with high programmability and flexibility to satisfy various micro-US studies. It incorporates a high-voltage arbitrary waveform generator for producing desired excitation waveform, and a programmable imaging receiver implemented by the state-of-the-art electronics and field-programmable gate array. Test results show that the proposed modulated excitation imaging system can acquire up to 20 dB signal-to-noise ratio improvement and 83% increase of penetration depth in contrast to traditional short-pulse imaging method. In vivo experiment on the dorsal skin of a human hand demonstrates good performance of the programmable modulated excitation imaging system. [ABSTRACT FROM PUBLISHER]

In this paper, time–frequency (TF) decomposition (TFD) is studied in the framework of sparse regularization theory. The short-time Fourier transform is first formulated as a convex constrained optimization where a mixed \ell1{-}\ell2 norm of the coefficients is minimized subject to a data fidelity constraint. Such formulation leads to a novel invertible decomposition with adjustable TF resolution. Then, a fast and efficient algorithm based on the alternating split Bregman technique is proposed to carry out the optimization with computational complexity [N^2 \log(N)]. Window length is a key parameter in windowed Fourier transform which affects the TF resolution; a novel method is also presented to determine the optimum window length for a given signal resulting to maximum compactness of energy in the TF domain. Numerical experiments show that the proposed sparsity-based TFD generates high-resolution TF maps for a wide range of signals having simple to complicated patterns in the TF domain. The performance of the proposed algorithm is also shown on real oil industry examples, such as ground roll noise attenuation and direct hydrocarbon detection from seismic data. [ABSTRACT FROM AUTHOR]

The strong noise produced by the leakage of electricity from marine seismic streamers is often received with seismic signals during marine seismic exploration. Traditional denoising methods show unsatisfactory effects when eliminating strong noise of this kind. Assuming that the strong noise signals have the same statistical properties, a blind source separation (BSS) algorithm is proposed in this paper that results in a new denoising algorithm based on the constrained multi-user kurtosis (MUK) optimization criterion. This method can separate strong noise that shares the same statistical properties as the seismic data records and then eliminate them. Theoretical and field data processing all show that the denoising algorithm, based on multi-user kurtosis optimization criterion, is valid for eliminating the strong noise which is produced by the leakage of electricity from the marine seismic streamer so as to preserve more effective signals and increase the signal-noise ratio. This method is feasible and widely applicable. [ABSTRACT FROM AUTHOR]

The development of very high data-rate power-line communication (PLC) systems requires an accurate knowledge of the transmission phenomena over the electrical network. In particular, the detection of the multiple propagation paths enables a compact description of the channel models, and gives an indication of the network topology, which may, in turn, be exploited to improve the communication techniques over PLC. In this paper, two high-resolution algorithms for the identification of the propagation paths are studied and adapted to the PLC channel characteristics, namely, the frequency-domain maximum-likelihood (FDML) algorithm and the Matrix Pencil (MP) algorithm. A parametric study is then detailed in order to analyze the performance of both algorithms in terms of resolution, computation time, and residual error. The study demonstrates that the MP algorithm provides a quicker convergence and a lower residual error when compared to the FDML algorithm. Finally, the MP algorithm is validated through its application on experimental network measurements. Results show a good agreement between the measurement and the synthetic channel recomposed from the detected paths. [ABSTRACT FROM AUTHOR]

Dual-energy computerized tomography has gained great interest because of its ability to characterize the chemical composition of a material rather than simply providing relative attenuation images as in conventional tomography. The purpose of this paper is to introduce a novel polychromatic dual-energy processing algorithm, with an emphasis on detection and characterization of piecewise constant objects embedded in an unknown cluttered background. Physical properties of the objects, particularly the Compton scattering and photoelectric absorption coefficients, are assumed to be known with some level of uncertainty. Our approach is based on a level-set representation of the characteristic function of the object and encompasses a number of regularization techniques for addressing both the prior information we have concerning the physical properties of the object and the fundamental physics-based limitations associated with our ability to jointly recover the Compton scattering and photoelectric absorption properties of the scene. In the absence of an object with appropriate physical properties, our approach returns a null characteristic function and, thus, can be viewed as simultaneously solving the detection and characterization problems. Unlike the vast majority of methods that define the level-set function nonparametrically, i.e., as a dense set of pixel values, we define our level set parametrically via radial basis functions and employ a Gauss–Newton-type algorithm for cost minimization. Numerical results show that the algorithm successfully detects objects of interest, finds their shape and location, and gives an adequate reconstruction of the background. [ABSTRACT FROM PUBLISHER]

A new algorithm is utilized to examine the phase and attenuation constants of open dissipative epsilon- and (or) mu-gyrotropic rod waveguides. Our algorithm allows analyzing the waveguides made of materials having very high losses. The dispersion characteristics of p-Ge with a waveguide of two component hole charge carders are calculated when the ratio of heavy hole concentration in the material is equal to 5%, 50% and 95% of the total free carrier concentration. The effective mass of p-Ge heavy and light holes are 0.279me and 0.043me respectively. The dispersion characteristics of the main and eight higher modes are presented in the paper. The transformation of higher hybrid modes at some heavy hole concentrations can be noticed. Waveguide broad bandwidth can be considerably extended due to the fact that the losses of higher modes are larger in comparison to those of the main mode at certain heavy hole concentration. [ABSTRACT FROM AUTHOR]

Abstract: Increasing demand of bandwidth in communication satellites has forced satellite links to be designed in Ku bands and above. But at these frequencies, rain and other tropospheric elements result in large attenuation. To mitigate the tropospheric attenuation of microwave satellite signals above 10GHz using any standard Fade Mitigation Technique (FMT), it is essential to have a priori knowledge about the level of attenuation. Hence, short-term rain attenuation prediction models play a key role in maintaining the link in which necessary compensation can be applied depending on the early information of attenuation. This paper presents a method of attenuation prediction using Adaptive Artificial Neural Network. Here In situ Learning Algorithm (ILA) has been used to enable the system to track the non-stationary nature of the attenuation. To validate this, Ku Band data, collected at three different sites in India have been used for the purpose of prediction. The performance of the algorithm is determined through the estimation of prediction accuracy by comparing the predicted values with the measured data. Results obtained using the mentioned technique shows considerably good accuracy even up to 20s of prediction interval with acceptable ratio between the under and over predictions. The prediction performance is evaluated for different prediction intervals. Furthermore the present model is also compared with the persistence model and the relative performance is quantified. [Copyright &y& Elsevier]

Abstract: Active noise control (ANC) is a methodology for attenuating noise based on adaptive signal processing algorithms. ANC is well assessed for the attenuation of Gaussian noise, but the rejection of non-Gaussian impulsive noise signals represents a much more critical task that may even impair algorithm convergence. To overcome this problem the adaptive filter weight update process must be modified by discarding or discounting samples associated with impulsive noise. This can be done either by modeling the impulsive noise with a non-Gaussian distribution such as the Symmetric -stable distribution or by applying an outlier detection method. With both approaches the accuracy in the noise description appears to be crucial for effective noise reduction. This paper proposes two novel approaches for the attenuation of impulsive noise both for invariant and time-varying noise distributions. The first one is based on the on-line estimation of an model of the noise probabilistic description. The second relies on a simple on-line recursive procedure that reliably estimates amplitude thresholds for outlier detection. Both methods compare favorably with competitor approaches, while maintaining a sufficiently low algorithm complexity. Several examples are shown to demonstrate the algorithms'' effectiveness. [Copyright &y& Elsevier]

Abstract: In this paper, we study a variant of the matching pursuit named matching pursuit shrinkage. Similar to the matching pursuit it seeks for an approximation of a datum living in a Hilbert space by a sparse linear expansion in a countable set of atoms. The difference with the usual matching pursuit is that, once an atom has been selected, we do not erase all the information along the direction of this atom. Doing so, we can evolve slowly along that direction. The goal is to attenuate the negative impact of bad atom selections. We analyze the link between the shrinkage function used by the algorithm and the fact that the result belongs to l 2, l 1 and l 0 space. Experimental results are also reported to show the potential application of the proposed algorithm. [Copyright &y& Elsevier]

Filtered backprojection is the basis for many CT reconstruction tasks. It assumes constant attenuation values of the object during the acquisition of the projection data. Reconstruction artifacts can arise if this assumption is violated. For example, contrast flow in perfusion imaging with C-arm CT systems, which have acquisition times of several seconds per C-arm rotation, can cause this violation. In this paper, we derived and validated a novel spatio-temporal model to describe these kinds of artifacts. The model separates the temporal dynamics due to contrast flow from the scan and reconstruction parameters. We introduced derivative-weighted point spread functions to describe the spatial spread of the artifacts. The model allows prediction of reconstruction artifacts for given temporal dynamics of the attenuation values. Furthermore, it can be used to systematically investigate the influence of different reconstruction parameters on the artifacts. We have shown that with optimized redundancy weighting function parameters the spatial spread of the artifacts around a typical arterial vessel can be reduced by about 70%. Finally, an inversion of our model could be used as the basis for novel dynamic reconstruction algorithms that further minimize these artifacts. [ABSTRACT FROM AUTHOR]

Abstract: The bent pipe wall thinning has been often found at the elbow of the drain line and the high-pressure secondary feed-water bent pipe in the nuclear reactors. The liquid droplet impingement (LDI) erosion could be regarded to be one of the major causes and is a significant issue of the thermal hydraulics and structural integrity in aging and life extension for nuclear power plants safety. In this paper two-phase numerical simulations are conducted for standard elbow geometry, typically the pipe diameter is 170mm. The turbulence attenuation in vapor-droplets flow is analysed by a damping function on the energy spectrum basis of single phase flow. Considering the vapor turbulent kinetic energy attenuation due to the involved droplets, a computational fluid dynamic (CFD) tool has been adopted by using two-way vapor-droplet coupled system. This computational fluid model is built up by incompressible Reynolds Averaged Navier–Stoke equations using standard k–ε model and the SIMPLE algorithm, and the numerical droplet model adopts the Lagrangian approach, a general LDI erosion prediction procedure for bent pipe geometry has been performed to supplement the CFD code. The liquid droplets diameter, velocity, volume concentration are evaluated for the effects of carrier turbulence attenuation. The result shows that carrier turbulence kinetic energy attenuation is proved to be an important effect for LDI erosion rate when investigating the bent pipe wall thinning phenomena. [Copyright &y& Elsevier]

The optimal microphone array, in the sense of minimum mean square errors (MMSE), includes two processing blocks: the minimum variance distortionless response (MVDR) beamformer and the single-channel Wiener filter, which acts as post-filter. In this paper, we propose a new post-filter algorithm based on assumptions that both the noise power attenuation factor (NPAF) and signal power attenuation factor (SPAF) are time invariant in the reverberant room. The algorithm recursively estimates both factors from available measurements and uses them in estimation of the post-filter parameters. Additionally, to overcome the problem of the poor performance of the MVDR beamformer in reverberant conditions, we propose the usage of the two-step (TS) MVDR algorithm. This algorithm improves the robustness of the beamformer and its ability to suppress the interferences using an estimate of the desired speaker transfer function. Although TS MVDR beamformer and proposed post-filter can work separately, or combined with other algorithms, the best performance is obtained when they work together. The performance of the proposed combination of new post-filter algorithm and TS MVDR beamformer is tested in a simulated reverberant room and compared with similar algorithms, which gave rather good results. [ABSTRACT FROM AUTHOR]

We present new results of the recently introduced approach to surface-multiple attenuation through sparse inversion. This method aims to attenuate surface multiples of all periodicities without the need for an adaptive subtraction or a near offset extrapolation. The aim of our paper is twofold. First, we subject the sparse inversion method to data beyond previously published proof-of-principle models and present results on highly complex 2D synthetics and real data, demonstrating that sparse inversion may, in principle, serve as a powerful tool to attenuate short and long period multiples in complex settings. We illustrate the competitive nature of the sparse inversion predictions by benchmarking the method's results to standard processing flows. In addition, we demonstrate the correspondence of the estimated primaries to the underlying impedance models. Next, we show results of a 2D sparse inversion approach to real 3D deep-marine data and demonstrate, through a further synthetic study, that the presence of cross-line dip leads to a time shift of the predicted multiples, resulting in reduced multiple attenuation. Our results confirm that future developments of this technique will require a full 3D approach in order for the sparse inversion method to be widely effective in practice. [ABSTRACT FROM AUTHOR]

Abstract: Active control of wide-band noise presents certain unique challenges many of which can be addressed using delayless subband adaptive filtering techniques. The performance of a delayless subband active noise control (DSANC) system depends on a complex interplay between the (1) choice of adaptation algorithm, (2) number of subbands, (3) weight stacking scheme, (4) input noise spectrum, and (5) primary, secondary paths. This interplay is studied in this paper for two different kinds of broadband noise. Distortion introduced by the weight stacking methods is investigated and quantified. It is shown that the computational complexity decreases and the stacking distortion increases with the number of subbands. The performance limiting effect of the non-minimum phase property of secondary path on the system performance is evaluated and analytically formulated. An upper bound for the obtainable noise attenuation level (NAL) is derived. A step by step optimal design procedure for the best performance is developed taking computational complexity into consideration. Simulation results support the analytical development and the proposed approach for optimal design of DSANC systems. [Copyright &y& Elsevier]

X-ray fluorescence computed tomography (XFCT) is a synchrotron-based imaging modality employed for mapping the distribution of elements within slices or volumes of intact specimens. A pencil beam of external radiation is used to stimulate emission of characteristic X-rays from within a sample, which is scanned and rotated through the pencil beam in a first-generation tomographic geometry. One limitation of XFCT is the long image acquisition time required to acquire a complete set of line integrals one-by-one. Typically, even if only a portion of a slice through the object is of interest, measurement lines are acquired spanning the entire object at every projection view over 180 degrees to avoid reconstructing images with so-called truncation artifacts. In this paper, we show that when attenuation is negligible, recent developments in tomographic reconstruction theory can be used to reduce the scanning effort required to reconstruct regions of interest within the slice. The new theory provides explicit guidance as to which line integrals must be measured for a given ROI and also provides a backprojection-filtration reconstruction algorithm that averts the truncation artifacts that typically plague filtered backprojection reconstructions from truncated data. This is demonstrated through simulation studies and with real synchrotron-based XFCT data. [ABSTRACT FROM AUTHOR]

Trajectory tracking or rejecting persistent disturbances with digital controllers in nonlinear processes is a class of problems where classical control methods breakdown since it is very difficult to describe the dynamic behavior over the entire trajectory. In this paper, a model-based robust control scheme is proposed as a potential solution approach for these systems. The proposed control algorithm is a robust error feedback controller that allows us to track predetermined operation profiles while attenuating the disturbances and maintaining the stability conditions of the nonlinear processes. Various numerical simulation examples demonstrate the effectiveness of this robust scheme. Two examples deal with effective trajectory tracking in chemical reactors over a wide range of operating conditions. The third example analyses the attenuation of periodic load in a biological reactor. All examples illustrate the ability of the robust control scheme to provide good control in the face of parameter uncertainties and load disturbances. [Copyright &y& Elsevier]

The FXLMS algorithm, used extensively in active noise control (ANC), exhibits frequency-dependent convergence behavior. This leads to degraded performance for time-varying tonal noise and noise with multiple stationary tones. Previous work by the authors proposed the eigenvalue equalization filtered-x least mean squares (EE-FXLMS) algorithm. For that algorithm, magnitude coefficients of the secondary path transfer function aremodified to decrease variation in the eigenvalues of the filtered-x autocorrelationmatrix, while preserving the phase, giving faster convergence and increasing overall attenuation. This paper revisits the EE-FXLMS algorithm, using a genetic algorithm to find magnitude coefficients that give the least variation in eigenvalues. This method overcomes some of the problems with implementing the EE-FXLMS algorithm arising from finite resolution of sampled systems. Experimental control results using the original secondary path model, and a modified secondary path model for both the previous implementation of EE-FXLMS and the genetic algorithm implementation are compared. [ABSTRACT FROM AUTHOR]

One of the problems concerned with active noise control is the existence of acoustical feedback between the control value ("active" loudspeaker output) and the reference signal. Various experiments show that such feedback can seriously decrease effects of attenuation or even make the whole ANC system unstable. This paper presents a detailed analysis of one of possible approaches allowing to deal with acoustical feedback, namely, virtual unidirectional sound source. With this method, two loudspeakers are used together with control algorithm assuring that the combined behaviour of the pair makes virtual propagation of sound only in one direction. Two different designs are presented for the application of active noise control in an acoustic duct: analytical (leading to fixed controller) and adaptive. The algorithm effectiveness in simulations and real experiments for both solutions is showed, discussed, and compared. [ABSTRACT FROM AUTHOR]

The Maseng-Bakken model simulates rain attenuation induced on a microwave link, and it accepts as input three parameters: the first two coincide with the parameters belonging to the conditional lognormal cumulative distribution of rain attenuation while the third one—called the dynamic parameter hereafter—should be assigned appropriately so that the model reflects some particular dynamic properties of rain attenuation. Thus far, the dynamic parameter has been calculated with emphasis on the simulation of the spectral density function of rain attenuation. This in turn, does not necessarily imply that the Maseng-Bakken model also simulates other crucial statistical features of rain attenuation such as Fade/Inter-Fade Duration Statistics. In this paper, we demonstrate a novel mathematical algorithm that gives the optimum value for the dynamic parameter so that the Maseng-Bakken model approximates simultaneously both second-order and hitting time statistics, with the latter being quite similar to Fade/Interfade durations. The algorithm is exemplified is through the simulation of rain attenuation affecting a satellite channel which operates at 20 GHz and connects Athens with Hellas-Sat 2. The results show that the optimum value for the dynamic parameter is much more "sensitive" to hitting time statistics—and probably to fade durations statistics as well—than it is to the spectral density function of rain attenuation. [ABSTRACT FROM AUTHOR]

In the field of digital signal processing, there are cases in which the frequency characteristics must be changed instantaneously in response to the processing objective. A filter whose characteristic can be varied instantaneously is called a variable filter. Many reports are available on the design of FIR digital filters with a variable passband. However, it appears that there are no publications on the design of an FIR digital filter in which the portion of the stopband with high attenuation can be varied. In this paper, a design method is proposed for an FIR digital filter using spectral parameters that make the portion of the stopband with high attenuation variable. For the design, the successive projection method with a simple algorithm is applied. A filter with an almost equal-ripple profile for the entire amplitude characteristic is designed by varying the spectral parameters. As a result, it is possible to obtain amplitude characteristics close to those of the filter solved by the Remez algorithm for specifications that change instantaneously from time to time. Finally, a design example is presented to confirm the effectiveness of the present approach. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(4): 34–41, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20176 [ABSTRACT FROM AUTHOR]

This paper deals with a systematical analysis and an algorithm of attenuation characteristics of a light attenuator combined by n pieces of polarizers (n-LACP) whose extinction ratios are different from each other. The attenuation ratio expression of a two-LACP is deduced. We find that the monotonic attenuation interval depends on the first polarizer and that the attenuation range depends on the second one. For the three-LACP, a method for obtaining a monotonic attenuation interval is proposed. Moreover, the attenuation ratio expression is demonstrated. Analysis and experiment show that when the initial status of the three-LACP is at the maximum output, if the second or third polarizer rotates alone, the minimum attenuation ratios can reach K2[?]1 and K3[?]1, respectively, and if the first polarizer rotates, a minimum attenuation ratio of K2[?]1K3[?]1 can be obtained (K1, K2 and K3 represent the extinction ratios of the three polarizers in turn). Furthermore, the attenuation ratio expression of n-LACP and the relevant attenuation characteristics are proposed. The minimum attenuation ratio of an n-LACP is (K2K3 *** Kn)[?]1. [ABSTRACT FROM AUTHOR]