Customer Reviews

Adaptive Blind Signal and Image Processing

5 star:		(2)
4 star:		(1)
3 star:		(0)
2 star:		(0)
1 star:		(0)

 

 

The previous reviewer is correct in that this is a huge tomb. However, since my purpose is to learn Blind Signal Decomposition, I will try to read another book first. I want to know one method before learning all possible methods.

Be warned -- there are many run-on sentences in this book. The authors like parenthetical expressions, as do I, but I'm not writing a book.

I find it difficult to read, because I have to keep trying to figure out what the author meants to say, instead of what they wrote.

It might just be me, but when I read about "dynamicAL systems" (as in Romeo and Juliet is Romantical), it breaks my concentration. Another problem I find is, "This is equal WITH that."

Oddly, the version I am reading states was "reprinted with corrections on April 2003, and Oct 2005". Yet is still has enough grammatical mistakes and very long sentences, to make reading difficult for me. I am glad I don't have the first printing.

Never before has such a large array of methods and algorithms for blind source
separation and independent component analysis (ICA) been put together
with such a coherent analysis.
The attached CD-ROM contains : MATLAB software and beautiful
interactive version of electronic book in pdf format
with precise illustrative fully colored figures and graphs.

Blind Signal and Image Processing is an exciting and emerging research topic in fields such
biomedical signal/image processing, advanced statistics, unsupervised adaptive filtering
and neural networks with solid theoretical foundations and many real world applications.
This book is practical and reference guide to wide spectrum of blind signal processing problems
including Independent Component Analysis (ICA), blind source separation (BSS),
blind recovery, blind signal extraction (BSE) and multi-channel blind deconvolution with
channel blind equalization (MBD/E).
The new corrected and fully revised edition (June 2003) consists of several revised features
and developments.
In my opinion, the most important features of the book include:
* Independent component analysis using various criteria, models and higher order statistics techniques
* Multistage robust blind separation of colored sources using second order statistics
* Robust blind decorrelation, whitening and orthogonalization
* Adaptive and information theoretic approaches to multi-channel blind deconvolution
with channel blind equalization
* Natural gradient, Stiefel manifolds and Lie group approaches
* Extended total and data least squares problems (ETLS/DLS)
* Sparse representation of signals, constrained matrix factorization and minimum p-norm problems
* MATLAB packages illustrating performance of a large number of ICA/BSS algorithms both
for signals and colored images.

Never before has such a large array of methods and algorithms for blind source
separation and independent component analysis (ICA) been put together
with such a coherent analysis.
The attached CD-ROM contains : MATLAB software and beautiful
interactive version of electronic book in pdf format
with with very illustrative fully colored figures and graphs.

Blind Signal and Image Processing is an exciting and emerging research topic in fields such
biomedical signal/image processing, advanced statistics, unsupervised adaptive filtering
and neural networks with solid theoretical foundations and many real world applications.
This book is practical and reference guide to wide spectrum of blind signal processing problems
including Independent Component Analysis (ICA), blind source separation (BSS),
blind recovery, blind signal extraction (BSE) and multi-channel blind deconvolution with
channel blind equalization (MBD/E).
The new corrected and fully revised edition (June 2003) consists of several revised features
and developments.
In my opinion, the most important features of the book include:
* Independent component analysis using various criteria, models and higher order statistics techniques

* Multistage robust blind separation of colored sources using second order statistics

* Robust blind decorrelation, whitening and orthogonalization

* Adaptive and information theoretic approaches to multi-channel blind deconvolution with channel blind equalization

* Natural gradient, Stiefel manifolds and Lie group approaches

* Extended total and data least squares problems (ETLS/DLS)

* Sparse representation of signals, constrained matrix factorization and minimum p-norm problems

* MATLAB packages illustrating performance of a large number of ICA/BSS algorithms both for signals and colored images.