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Adaptive Filter Theory (4th Edition)
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Author: Simon Haykin
List Price: $116.00
Our Price: Click to see the latest and low price
ISBN: 0130901261
Publisher: Prentice Hall (14 September, 2001)
Edition: Hardcover
Sales Rank: 212,852
Average Customer Rating: 4.2 out of 5
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Customer ReviewsRating: 5 out of 5
A very good book for Adaptive DSP...
I have always wondered why many people have negative opinions about books by Simon Haykin, whether it is 'Communication Systems' or 'Adaptive Filter Theory'. Particularly, this book 'Adaptive Filter Theory', in my opinion, is one of the bestbooks on this subject. As Julius Kusuma correctly mentioned, this book is indeed an "adventure ride" into the field of Adaptive Filter Theory.I discovered this book when I was doing a class project on Self-Orthogonalizing algorithms for Adaptive Beamforming and I felt that all the relevant information that I needed was present in this book. I did'nt really feel the neccesity to refer anything outside this book. Apart from that, this book contains everything that a graduate student needs to know about this exciting field of adaptive filters. The author assumes some background on Random Signal Theory... I'd suggest to look up Sam Shanmugan et al's, "Random Signals: Detection, Estimation and Data Analysis" before beginning to read (enjoy) this "adventure ride" on Adaptive Filters.
Rating: 5 out of 5
Adventures in the development of stochastic DSP
Despite the commonly negative opinion against Simon Haykin's book, I find this book to be a very fun reading. It starts off with a very brief review of DSP (more useful just for getting familiar with the notation, really), properties of random processes, and a small section on linear algebra in the middle of the book. The rest of the book can be viewed as a story of how different approaches and algorithms were developed, and is a little difficult to use as reference due to its lack of structure and over-dependency on the previous chapters, both for technical content and notation. But there's a lot of hidden treasures within this book that should have been more emphasized. For example, Mold's theorem that states that any discrete stationary process can be decomposed into a deterministic component and a random component, which are uncorrelated to each other. I'm sorry, but a reference to a proof in another book is not enough to really motivate me. This is a very fundamental theorem if you're interested in stochastic signal processing. Sure, you don't cover the Fundamental Theorem of Calculus in your very first calculus class, but then again this is supposed to be a fairly advanced book. So if you're interested in learning certain things quickly, this is NOT the book to get. Consider Munson Hayes' book instead. Save this one when you feel like investing a little time to hear Haykin's story on stochastic signal processing.
Rating: 3 out of 5
Good book if you are an expert!
Before start reading this book, read "Uderstanding Digital Signal Processing" by Lyons first.
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