Nonnegative Matrix and Tensor Factorizations (eBook)

Andrzej Cichocki, Laboratory for Advanced Brain Signal Processing, Riken Brain Science Institute, Japan Professor Cichocki is head of the Laboratory for Advanced Brain Signal Processing. He has co-authored more than one hundred technical papers, and is the author of three previous books of which two are published by Wiley. His most recent book is Adaptive Blind Signal and Image Processing with Professor Shun-ichi Amari (Wiley, 2002). He is Editor-in-Chief of International Journal Computational Intelligence and Neuroscience and Associate Editor of IEEE Transactions on Neural Networks. Shun-ichi Amari, Laboratory for Mathematical Neuroscience, Riken Brain Science Institute, Japan Professor Amari is head of the Laboratory for Mathematical Neuroscience, as well as vice-president of the Riken Brain Science Institute. He serves on editorial boards for numerous journals including Applied Intelligence, Journal of Mathematical Systems and Control and Annals of Institute of Statistical Mathematics. He is the co-author of three books, and more than three hundred technical papers. Rafal Zdunek, Institute of Telecommunications, Teleinformatics and Acoustics, Wroclaw University of Technology, Poland Associate Professor Zdunek is currently a lecturer at the Wroclaw University of Technology, Poland and up until recently was a visiting research scientist at the Riken Brain Science Institute. He is a member of the IEEE: Signal Processing Society, Communications Society and a member of the Society of Polish Electrical Engineers. Dr Zdunek has guest co-edited with Professor Cichocki amongst others, a special issue on Advances in Non-negative Matrix and Tensor Factorization in the journal, Computational Intelligence and Neuroscience (published May 08). Anh Huy Phan, Laboratory for Advanced Brain Signal Processing, Riken Brain Science Institute, Japan Anh Huy Phan is a researcher at the Laboratory for Advanced Brian Signal Processing at the Riken Brain Science Institute.

"[A] focus on the algorithms that are most useful in practice and aim to derive and implement, in MATLAB, efficient and simple iterative algorithms that work with real-world data." (Book News, December 2009)