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Independent Component Analysis

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ISBN-10: 047140540X

ISBN-13: 9780471405405

Edition: 2001

Authors: Aapo Hyv�rinen, Juha Karhunen, Erkki Oja, Aapo Hyv�rinen

List price: $209.95
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Independent Component Analysis (ICA) is a statistical technique for revealing hidden factors from multiple measurements. This is an emerging field with potentially important applications in medical imaging, data mining and beam forming.
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Book details

List price: $209.95
Copyright year: 2001
Publisher: John Wiley & Sons, Incorporated
Publication date: 6/1/2001
Binding: Hardcover
Pages: 504
Size: 6.40" wide x 9.50" long x 1.15" tall
Weight: 1.782
Language: English

AAPO HYV�RINEN, PhD, is Senior Fellow of the Academy of Finland and works at the Neural Networks Research Center of Helsinki University of Technology in Finland. JUHA KARHUNEN and ERKKI OJA are professors at the Neural Networks Research Center of Helsinki University of Technology in Finland.

Preface
Introduction
Mathematical Preliminaries
Random Vectors and Independence
Gradients and Optimization Methods
Estimation Theory
Information Theory
Principal Component Analysis and Whitening
Basic Independent Component Analysis
What is Independent Component Analysis?
ICA by Maximization of Nongaussianity
ICA by Maximum Likelihood Estimation
ICA by Minimization of Mutual Information
ICA by Tensorial Methods
ICA by Nonlinear Decorrelation and Nonlinear PCA
Practical Considerations
Overview and Comparison of Basic ICA Methods
Extensions and Related Methods
Noisy ICA
ICA with Overcomplete Bases
Nonlinear ICA
Methods using Time Structure
Convolutive Mixtures and Blind Deconvolution
Other Extensions
Applications of ICA
Feature Extraction by ICA
Brain Imaging Applications
Telecommunications
Other Applications
References
Index
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