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Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, R&D engineers and graduates wishing to learn the core principles, methods, algorithms, and applications of Blind Source Separation.
Introduction; Information; Contrast functions; Likelihood; Algebraic methods after prewhitening; Iterative algorithms; Second order methods based on color; Convolutive mixtures; Algebraic identification of under-determined mixtures; Sparse component analysis; Quadratic time-frequency domain methods; Bayesian approaches; Non-negative mixtures; Nonlinear mixtures; Semi-blind methods for communications; Overview of source separation applications; Application to telecommunications; Biomedical applications; Audio applications
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