Information Theory, Inference and Learning Algorithms

Critically acclaimed since its inception, "Advances in Librarianship" continues to be the essential reference source for developments in the field of libraries and library science. Articles published in the Series have won national prizes, such as the recent Blackwell North America Scholarship Award for the outstanding 1994 monograph, article, or original paper in the field of acquisitions, collection, development, and related areas of resource development. All areas of public, college, university, primary and secondary schools, and special libraries are given up-to-date, critical analysis by experts engaged in the practice of librarianship, in teaching, and in research. Written by professionals for professionals to find solutions to vexing questions, it is authoritative, in-depth, and concise, and the single best source for keeping up-to-date on key issues.

<p>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. </p>

Loshin, Peter

Wu, Zhijun

Yang, Xin-She

Lin, Shu