Description: Nonnegative Matrix and Tensor Factorizations : Applications to Exploratory Multi-Way Data Analysis and Blind Source Separation, Hardcover by Cichocki, Andrzej; Zdunek, Rafal; Phan, Anh Huy; Amari, Shun-Ichi, ISBN 0470746661, ISBN-13 9780470746660, Like New Used, Free shipping in the US Cichocki (advanced brain signal processing, Riken Brain Institute, Japan, and Warsaw U. of Technology and Systems Research Institute, PAN, Poland) et al. provide a survey of models and efficient algorithms for nonnegative matrix factorization, including extensions and modifications, especially nonnegative tensor factorizations and nonnegative Tucker decompositions. They 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. Included is discussion of iterative multiplicative algorithms, alternating least squares algorithms, projected gradient algorithms, learning algorithms, and selected applications such as data clustering, text mining, email surveillance, musical instrument classification, face recognition, spectroscopy, imaging, and gene expression classification. Th is meant for engineers, researchers, scientists, industry practitioners, and graduate students in signal and image processing, neuroscience, data mining and analysis, computer science, bioinformatics, speech processing, biomedical engineering, and multimedia. Annotation ©2009 Book News, Inc., Portland, OR ()
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Book Title: Nonnegative Matrix and Tensor Factorizations : Applications to Ex
Number of Pages: 504 Pages
Language: English
Publication Name: Nonnegative Matrix and Tensor Factorizations : Applications to Exploratory Multi-Way Data Analysis and Blind Source Separation
Publisher: Wiley & Sons, Incorporated, John
Item Height: 1.2 in
Subject: Waves & Wave Mechanics, Programming / General, Programming / Algorithms, Databases / Data Mining
Publication Year: 2009
Type: Textbook
Item Weight: 42.5 Oz
Author: Rafal Zdunek, Andrzej Cichocki, Anh Huy Phan, Shun-Ichi Amari
Item Length: 9.9 in
Subject Area: Computers, Science
Item Width: 6.8 in
Format: Hardcover
