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Handbook of Blind Source Separation: Independent Component Analysis and Blind Deconvolution
By: Pierre Comon , Christian JuttenImprint: Academic Press
Format: ePub Encrypted (DRM)
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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.
Covers the principles and major techniques and methods in one book
Edited by the pioneers in the field with contributions from 34 of the world's experts
Describes the main existing numerical algorithms and gives practical advice on their design
Covers the latest cutting edge topics: second order methods; algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communications
Shows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications
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| Title of Computers eBook: Handbook of Blind Source Separation: Independent Component Analysis and Blind Deconvolution | |
| Release Date: 01-01-2010 | |
| Publisher: Academic Press |
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Handbook of Blind Source Separation: Independent Component Analysis and Blind Deconvolution
Chapter One
IntroductionC. Jutten and P. Comon
Blind techniques were born in the 1980s, when the first adaptive equalizers were designed for digital communications. The problem was to compensate for the effects of an unknown linear single input single output (SISO) stationary channel, without knowing the input.
The scientific community used the word "blind" for denoting all identification or inversion methods based on output observations only. In fact, blind techniques in digital communications aimed at working when the "eye was closed"; hence the terminology.
At the beginning, the word "unsupervised" was sometimes used (for instance in French the wording autodidacte), but it seems now better to be consistent with the worldwide terminology, even if this is not ideal, since comprehensible only in the context of digital communications.
The problem of blind source separation (BSS) differs from blind equalization, addressed previously by Sato, Godard and Benveniste, by the fact that the unknown linear system consists of several inputs and outputs: such a system is referred to as multiple inputs multiple outputs (MIMO). Initially restricted to memoryless channels, the BSS problem now encompasses all linear or nonlinear MIMO mixtures, with or without memory.
The BSS problem was first formulated in 1984, although theoretical principles, which drive source separation methods, were understood later. In this chapter, we briefly introduce the principles and main notations used in this book. A few ideas which contributed to the development of this research domain from its birth are reviewed. The present chapter
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