Blind Signal Processing Theory and Applications(Chinese Edition)
LIU JU . SUN JIAN DE . XU HONG JI
Sold by liu xing, Nanjing, JS, China
AbeBooks Seller since April 7, 2009
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Add to basketSold by liu xing, Nanjing, JS, China
AbeBooks Seller since April 7, 2009
Condition: New
Quantity: 1 available
Add to basketShip out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.Paperback. Pub Date: 2013 Pages: 319 Language: Chinese in Publisher: Science Press blind signal processing theory and application on the basis of years of research on blind source separation theory and its application in the relevant field elaboration. pay attention to the combination of theory and practice. provide examples and simulation results to help readers' understanding of the theory of blind signal processing; same time. pay attention to the introduction of cutting-edge technology in the field of blind signal processing enables readers to understand the field the latest developments and trends. Britannica main contents include: Blind signal separation and independent component analysis of the basic concepts and theory. stochastic processes and information theory. blind separation and blind deconvolution method. speech signal blind separation of a real environment. image and video based on independent component analysis digital watermark. the space-time wireless communication system blind detection and blind signal separation methods in biomedical signal processing applications. Blind signal processing theory and application of scientific and technical personnel engaged in the study of signal processing available reference can also be an important reference book as institutions of higher learning communication. electronics. information. automation. and biomedical engineering professional teachers and graduate study blind signal processing theory . Contents: Preface Chapter 1 blind signal processing infrastructure 1.1 Overview 1.1.1 Background and status quo at home and abroad the 1.1.2 book 1.2 blind source separation problem description and mathematical model 1.2.1 blind source separation and blind deconvolution system mathematical the model 1.2.2 blind identification uncertainty and identifiability 1.3 blind signal processing mathematical foundation 1.3.1 random process foundation 1.3.2 Information theoretical foundation 1.3.3 used in blind signal processing optimization method References Chapter 2 blind source separation method 2.1 2.1.1 Overview 2.1.2 Mutual cumulative amount criterion 2.1.3 diagonal cumulants guidelines and algorithms 2.1.4 based on the cumulative amount of unconstrained algorithm of blind source separation method based on higher order statistics 2.1.5 based on a simple go redundant source signal extraction method individually 2.2 blind source separation methods based on information theory 2.2.1 Overview 2.2.3 minimum criteria based on information redundancy and algorithm 2.2.4 2.2.2 based on negative entropy minimum mutual information criterion and algorithm nonlinear blind source separation method based on multivariate density estimates 2.3 the aliasing blind signal separation 2.3.1 Introduction 2.3.2 Separability and solutions not only 2.3.3 multilayer perceptron-based information and reference to the propagation algorithm Chapter 3 real environmental voice signal blind separation of 3.1 with noise aliasing speech signal blind separation 3.1.1 based on wavelet transform and ICA Noisy speech signal aliasing blind separation 3.1.2 sparse coding and ICA-based blind Noisy Speech Signal ICA-based microphone voice signal separation of 3.2 based on microphone array to enhance the spatial coherence of the noise field method 3.2.1 microphone array structure 3.2.2 microphone array speech processing technology 3.2.3 3.2.4 classic microphone array speech enhancement method 3.2.5 array speech enhancement system 3.2.6 computer simulation and performance analysis 3.3 voice signal aliasing blind separation 3.3.1 system model and estimated mixing matrix priori assumptions 3.3.2 System Block Diagram 3.3.3 3.3.4 source signal due to the given situation estimated the 3.3.5 computer simulation and performance analysis of the speech signal blind separation 3.4 Convolution aliasing 3.4.1 Overview 3.4.2 the observed.
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