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Independent Component Analysis, by Aapo Hyvärinen, Juha Karhunen, Erkki Oja
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A comprehensive introduction to ICA for students and practitioners
Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more.
Independent Component Analysis is divided into four sections that cover:
* General mathematical concepts utilized in the book
* The basic ICA model and its solution
* Various extensions of the basic ICA model
* Real-world applications for ICA models
Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.
- Sales Rank: #1208121 in Books
- Published on: 2001-05-18
- Original language: English
- Number of items: 1
- Dimensions: 9.50" h x 1.15" w x 6.40" l, 1.80 pounds
- Binding: Hardcover
- 504 pages
Review
"...researchers...introduce independent component analysis as a statistical and computational technique for revealing hidden factors that underlie sets of random variables, measurements, or signals." (SciTech Book News, Vol. 25, No. 4, December 2001)
From the Back Cover
A comprehensive introduction to ICA for students and practitioners
Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more.
Independent Component Analysis is divided into four sections that cover:
* General mathematical concepts utilized in the book
* The basic ICA model and its solution
* Various extensions of the basic ICA model
* Real-world applications for ICA models
Authors Hyvärinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.
About the Author
AAPO HYVÄRINEN, 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.
Most helpful customer reviews
23 of 27 people found the following review helpful.
Comprehensive Book
By khaled
Independent Component Analysis is a young and interesting topic that gained attention and still receiving more of it.
Until now this is the best introduction that has been written.
It is comprehensive, clear and unbiased.
I think that the book is a step toward making the subject not only a common field of research but also a reference for those looking for new challenging topics.
What worths mentioning is that the authors are very envolved in the development of the theory of ICA ,other books are good but are deviated by their author's own approachs and this is normal but unhealthy for a first book on any field.
What constitutes a great help for understanding ICA are the relatively easy concepts if one just intend to pick an algorithm(ex:FastICA), but this is not the case regarding its theory.
One colleague once argued that ICA should have emerged long before the begining of the 90's, claiming that Gaussian forms
(Central Limit-Theorem) killed the idea of dealing with other kinds of distributions and therefore the signal processing community went assuming every thing was gaussian (noise was gaussian,signals are gaussian),but the emerge of HOS relaxed the gaussian restriction and ICA became possible and no longer 'blind' .
I think this should prepare researchers to deal with coming challengs more intelligently and efficiently .That is why I recommend this book since it tries to give a broad view to the subject .
9 of 12 people found the following review helpful.
Nice and detailed description of ICA
By A Customer
This is a nice and self-contained book on the subject of independent component analysis (ICA). The authors start with relevant mathematical and statistical background (in Part I) to prepare readers for the derivations of ICA (though seasoned researchers may want to skip the first part of this book). The authors discuss the motivation behind ICA and present several ways to derive ICA (since this subject has been approached by several communities). The authors also compare and discuss the pros and cons of these approaches. The authors discuss several applications using ICA in Part III.
Compared with other ICA books, this manuscript has much depth and completeness. I highly recommend this book to any reader interested in this topic.
0 of 0 people found the following review helpful.
Five Stars
By Amazon Customer
Very nice book for independent component analysis (ICA) algorithms.
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