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共 465 条记录，以下是171-180 订阅

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New matrix decomposition based on transforming the basis sets of the singular value decomposition yields principal features for time-frequency distributions

New matrix decomposition based on transforming the basis set...

引用

Advance signal processing algorithms, Atchitectures, and implementations X

作者： Groutage, Dale Bennink, David Naval Surface Warfare Cent Bremerton United States

We present a matrix decomposition that can be used to derive features from processes that are described by discrete-time, time-frequency representations. These include, among others, electrocardiograms, brain wave signals, seismic signals, vibration and shock signals, speech signals for voice recognition, and acoustic transient signals. The new decomposition is based on a transformation of the basis vectors of the singular value decomposition (SVD) which we call transformed singular value decomposition or TSVD. The transformed basis vectors are obtained by forming linear combinations of the original SVD basis vectors in a way such that the means of the transformed vectors are extrema of each other. The TSVD basis vectors are used to identify concentrations of energy density in the discrete-time, time-frequency representation by time and frequency descriptors. That is, descriptors such as the location in time, the spread in time, the location in frequency and the spread in frequency for each principal concentration of energy density can be obtained from the TSVD terms in the matrix decomposition series. Several examples are presented which illustrate the application of the new matrix decomposition for deriving principal time and frequency features from the discrete-time, time-frequency representations of nonstationary processes. Two of the examples illustrate how the derived time and frequency features can be used to classify individual short duration transient signals into respective classes, that is,: (1) automatically classify sonar signals as belonging to one of ten classes, and (2) automatically classify heartbeat signals as belonging to one of two people.

关键词： signal processing

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Systematic architecture exploration for implementing interference suppression techniques in wireless receivers

Systematic architecture exploration for implementing interfe...

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IEEE Workshop on signal processing Systems (SIPS)

作者： Ning Zhang B. Haller R. Brodersen Wireless Research Laboratory Lucent Technologies Inc. USA Berkeley Wireless Research Center Department of EECS University of California Berkeley USA

Future wireless systems are required to provide higher data rates, improved spectral efficiency and greater capacity. This can be achieved at the cost of increased signal processing complexity. The successful implementation of advanced algorithms and dedicated hardware architectures to tackle the demanding signal processing tasks calls for an integrated development process. It must effectively exploit the many interrelations between the different levels of the design hierarchy and efficiently bridge the gap between system concepts and their VLSI circuit realization. This paper presents the algorithm and architecture level design of interference suppression techniques for advanced wireless receivers based on the use of multiple antenna elements in combination with appropriate signal combining. A systematic approach to architecture exploration is demonstrated which leads to efficient implementations in terms of both power consumption and silicon area.

关键词： signal processing algorithms Costs Hardware Bridge circuits Very large scale integration signal design Algorithm design and analysis Interference suppression Receiving antennas Energy consumption

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Nonlinear biomedical signal processing /

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2000年

作者： edited by Metin Akay.

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Nonlinear Biomedical signal processing 1

引用

丛书名： IEEE Press Series on Biomedical Engineering) (Volume 2

2000年

作者： Akay, Metin

ISBN: (数字)9780470545379

ISBN: (纸本)9780780360129

Featuring current contributions by experts in signal processing and biomedical engineering, this book introduces the concepts, recent advances, and implementations of nonlinear dynamic analysis methods. Together with Volume I in this series, this book provides comprehensive coverage of nonlinear signal and image processing techniques. "Nonlinear Biomedical signal processing: Volume ii" combines analytical and biological expertise in the original mathematical simulation and modeling of physiological systems. Detailed discussions of the analysis of steady-state and dynamic systems, discrete-time system theory, and discrete modeling of continuous-time systems are provided. Biomedical examples include the analysis of the respiratory control system, the dynamics of cardiac muscle and the cardiorespiratory function, and neural firing patterns in auditory and vision systems. Examples include relevant MATLAB(R) and Pascal programs. Topics covered include: LI Nonlinear dynamics LI Behavior and estimation LI Modeling of biomedical signals and systems LI Heart rate variability measures, models, and signal assessments LI Origin of chaos in cardiovascular and gastric myoelectrical activity LI Measurement of spatio-temporal dynamics of human epileptic seizures A valuable reference book for medical researchers, medical faculty, and advanced graduate students, it is also essential reading for practicing biomedical engineers. "Nonlinear Biomedical signal processing, Volume ii" is an excellent companion to Dr. Akay's "Nonlinear Biomedical signal processing, Volume I: Fuzzy Logic, Neural Networks, and New algorithms."

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advanced signal processing algorithms, architectures and implementations

Advanced Signal Processing Algorithms, Architectures and Imp...

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1999年

作者： Franklin T Luk

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FPOP: Field Programmable On-line oPerators

FPOP: Field Programmable On-line oPerators

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Conference on advanced signal processing algorithms, architectures, and implementations IX

作者： Tisserand, A Marchal, P Piguet, C CSEM Neuchatel Switzerland

ISBN: (纸本)0819432938

This paper describes a new digital reprogrammable architecture called Field Programmable On-line oPerators (FPOP). This architecture is a kind of FPGA dedicated to very low-power implementations of numerical algorithms in signal processing or digital control applications for embedded or portable systems. FPOP is based on a reprogrammable array of on-line arithmetic operators. On-line arithmetic is a digit-serial arithmetic with most significant digits first using a redundant number system. Because of the small size of the digit-serial operators and the small number of communication wires between the operators, single chip implementation of complex numerical algorithms can be achieved using on-line arithmetic. Furthermore, the digit-level pipeline and the small size of the arithmetic operators lead to high-performance parallel computations. Compared to a standard FPGA, the basic cells in FPOP are arithmetic operators such as adders, subtracters, multipliers, dividers, square-rooters, sine or cosine operators. This granularity level allows very efficient power x delay implementations of most algorithms used in digital control and signal processing. The circuit also integrates some analog to digital and digital to analog converters.

关键词： FPGA reconfigurable logic on-line arithmetic digital control signal processing

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Blind decorrelation and deconvolution algorithm for multiple input multiple output system ii - Analysis and simulation

Blind decorrelation and deconvolution algorithm for multiple...

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Conference on advanced signal processing algorithms, architectures, and implementations IX

作者： Chen, DC Yu, T Yao, K Pottie, G Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

ISBN: (纸本)0819432938

For single-input multiple-output (SIMO) systems blind deconvolution based on second-order statistics has been shown promising given that the sources and channels meet certain assumptions. In our previous paper we extend the work to multiple-input multiple-output (MIMO) systems by introducing a blind deconvolution algorithm to remove all channel dispersion followed by a blind decorrelation algorithm to separate different sources from their instantaneous mixture. In this paper we first explore more details embedded in our algorithm. Then we present simulation results to show that our algorithm is applicable to MIMO systems excited by a broad class of signals such as speech, music and digitally modulated symbols.

关键词： blind deconolution blind decorrelation

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Generalized reaction-diffusion equation for image processing

Generalized reaction-diffusion equation for image processing

引用

Conference on advanced signal processing algorithms, architectures, and implementations IX

作者： Wei, GW Natl Univ Singapore Dept Computat Sci Singapore Singapore

ISBN: (纸本)0819432938

This paper presents a robust algorithm for image processing using generalized reaction-diffusion equations. An edge enhancing functional is proposed for image enhancement. A number of super diffusion operators is introduced for fast and effective smoothing. Statistical information is utilized for robust edge-stopping and diffusion rate estimation. A unification of computational methods is discussed. The unified computational method is employed for the numerical integration of the generalized reaction-diffusion equations. Computer experiments indicate that the present algorithm is very efficient for edge-detecting and noise-removing.

关键词： image processing generalized reaction-diffusion equations unified computational method

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Denoising using time-frequency and image processing methods

Denoising using time-frequency and image processing methods

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Conference on advanced signal processing algorithms, architectures, and implementations IX

作者： Nelson, D Cristóbal, G Kober, V Cakrak, F Loughlin, P Cohen, L US Dept Def Ft Meade MD 20755 USA

ISBN: (纸本)0819432938

We present a number of methods that use image and signed processing techniques for removal of noise from a signal. The basic idea is to first construct a time-frequency density of the noisy signal. The time-frequency density, which is a function of two variables, can then be treated as an "image", thereby enabling use of image processing methods to remove noise and enhance the image. Having obtained an enhanced time-frequency density, one then reconstructs the signal. Various time frequency-densities are used and also a number of image processing methods are investigated. Examples of human speech and whale sounds are given. In addition, new methods are presented for estimation of signal parameters from the time-frequency density.

关键词： Electronic filtering Interference (communication) Fourier transforms Time-frequency analysis Frequency modulation Fermium Transform theory signal processing Optical filters Filtering (signal processing)

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Identification of a multicomponent signal by a TEA scheme operating in the Time-Frequency plane

Identification of a multicomponent signal by a TEA scheme op...

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Conference on advanced signal processing algorithms, architectures, and implementations IX

作者： Lo Presti, L Olmo, G Galleani, L Politecn Torino Dipartimento Elettron I-10129 Turin Italy

ISBN: (纸本)0819432938

In this paper, a method for signal component separation, operating in the Time-Frequency (TF) plane and employing a Turbo Estimation Algorithm (TEA), is described. A novel 2D distribution is proposed, named Two Window Spectrogram (TWS), which is free from crossterms and able to yield good time anti frequency resolution. Then, a set of parameters is defined in the time-frequency plane, which are able to carry the relevant information on the signal components. An algorithm of estimation of these parameters is proposed, making use of a TEA scheme to yield improved performance. The algorithm has been tested by simulation, yielding very encouraging performance.

关键词： Thermal weapon sites Time-frequency analysis Detection theory Interference (communication) Prototyping signal processing signal to noise ratio Tantalum Yield improvement Fourier transforms

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