Adaptive Filtering: Algorithms and Practical Implementation Review

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(More customer reviews)The book by Prof. Diniz is indeed amongst the best on adaptive signal processing. Most of the fundamental concepts are well explained, suitable examples are given and practical applications are also discussed. The chapter on adaptive IIR filters is unique and still cannot be found in any other book. Moreover, solutions to the problems can be obtained by ftp, which is something very useful for students. Despite this is an excellent book (5 star), the price is ridiculous, as occurs with most titles from this publisher. If I were Prof. Diniz I would change from Kluwer Academic Publishers to a more competitive publisher.

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This book presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner, using clear notations that facilitate actual implementation. Important algorithms are described in detailed tables which allow the reader to verify learned concepts. The book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, IIR adaptive filtering, and more. Includes a CD supplement for instructors and students, offering lecture transparencies as well as MATLAB codes for all algorithms described in the text. The book is also supported by a web page maintained by the author.

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Statistical Digital Signal Processing and Modeling Review

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(More customer reviews)I used this book to learn nearly all the topics covered in a hurry, in order to take the prelim exam at Berkeley. While it was a humbling experience, it made me truly learn to appreciate and love this book, and its great presentation and organization.
It starts off with a very good introduction to linear algebra and probability theory for engineers, which should give you a taste of the effective way that this book is laid out. The format is excellent, and the important points clearly highlighted. This is a real joy to read!
The magic doesn't wear off into the later chapters, which include topics in signal modeling, least-squares methods, MMSE estimation, Levinson algorithm, spectral estimation, and adaptive filters.
I find this book to be a great source for both learning and reference, and as a bonus it includes Matlab codes for all the algorithms mentioned here.
One complain is that there are certain topics that could be covered more effectively. For example, the relationship between the different signal models and filtering is not mentioned, and this could help understand the motivation of the different signal models in the first place.
Anyway, once you get past Oppenheim/Schafer, Proakis/Manolakis and Lyons' material this can be a great way to start your journey into the more advanced topics in signal processing.

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The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering. Scores of worked examples illustrate fine points, compare techniques and algorithms and facilitate comprehension of fundamental concepts. Also features an abundance of interesting and challenging problems at the end of every chapter.

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