Handbook of Blind Source Separation: Independent Component Analysis and Applications - Tapa dura

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

Christian Jutten received a PhD degree in 1981 and the Docteur es Sciences degree in 1987 from the Institut National Polytechnique of Grenoble (France). He is currently deputy director of Institute for Information Sciences and Technologies of CNRS. He has been deputy director of the Grenoble images, speech, signal and control laboratory (GIPSA) and director of the Department Images-Signal (DIS from 2007 to 2010. For 30 years, his research interests have been blind source separation, independent component analysis and learning in neural networks, including theoretical aspects (separability, source separation in nonlinear mixtures, sparsity) and applications in signal processing (biomedical, seismic, hyperspectral imaging, speech). He is author or co-author of more than 75 papers in international journals, four books, 25 invited plenary talks and 170 communications in international conferences. He received the Medal Blondel in 1997 from SEE (French Electrical Engineering society) for his contributions in source separation and independent component analysis, and has been elevated as a Fellow IEEE and a senior Member of Institut Universitaire de France in 2008. In 2012, he was awarded by an ERC Advanced Grant CHESS. In 2013, he has been elevated as EURASIP Fellow and reconducted for five years as a senior member of Institut Universitaire de France.