Adaptive Blind Signal and Image Processing
Learning Algorithms and Applications
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Adaptive Blind Signal and Image Processing by Andrzej Cichocki
Book DescriptionWith solid theoretical foundations and numerous potential applications, Blind Signal Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume unifies and extends the theories of adaptive blind signal and image processing and provides practical and efficient algorithms for blind source separation, Independent, Principal, Minor Component Analysis, and Multichannel Blind Deconvolution (MBD) and Equalization. Containing over 1400 references and mathematical expressions, "Adaptive Blind Signal and Image Processing" delivers an unprecedented collection of useful techniques for adaptive blind signal/image separation, extraction, decomposition and filtering of multi variable signals and data. It offers a broad coverage of blind signal processing techniques and algorithms both from a theoretical and practical point of view. It presents more than 50 simple algorithms that can be easily modified to suit the reader's specific real world problems. It provides a guide to fundamental mathematics of multi input, multi output and multi sensory systems. It includes illustrative worked examples, computer simulations, tables, detailed graphs and conceptual models within self contained chapters to assist self study. An accompanying CD-ROM features an electronic, interactive version of the book with fully coloured figures and text. C and MATLAB[registered] user friendly software packages are also provided. MATLAB[registered] is a registered trademark of The MathWorks, Inc. By providing a detailed introduction to BSP, as well as presenting new results and recent developments, this informative and inspiring work will appeal to researchers, postgraduate students, engineers and scientists working in biomedical engineering, communications, electronics, computer science, optimisations, finance, geophysics and neural networks.
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Book DetailsISBN: 9780471607915
(245mm x 174mm x 38mm)
Imprint: John Wiley & Sons Ltd
Publisher: John Wiley and Sons Ltd
Publish Date: 26-Apr-2002
Country of Publication: United Kingdom
Books By Author Andrzej Cichocki
Non-negative Matrix and Tensor Factorizations, Hardback (September 2009)
This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF's various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD).
Neural Networks for Optimization and Signal Processing, Hardback (April 1993)» View all books by Andrzej Cichocki
A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but also to create new techniques and architectures. Provides in-depth coverage of mathematical modeling along with illustrative computer simulation results.
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