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Fundamentals of Adaptive Filtering
 
 
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Fundamentals of Adaptive Filtering [Hardcover]

Ali H. Sayed (Author)
4.6 out of 5 stars  See all reviews (10 customer reviews)

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Book Description

0471461261 978-0471461265 June 13, 2003 1
This book is based on a graduate level course offered by the author at UCLA and has been classed tested there and at other universities over a number of years. This will be the most comprehensive book on the market today providing instructors a wide choice in designing their courses.
* Offers computer problems to illustrate real life applications for students and professionals alike
* An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.


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Editorial Reviews

Review

"...a remarkably clear, accessible, and up-to-date text. It is highly recommended for students at the graduate level…is an invaluable and comprehensive reference…for researchers at all levels." (IEEE Control Systems Magazine, August 2005)

From the Back Cover

The most comprehensive treatment of adaptive filtering available

Here is a fresh, broad, and systematic treatment of adaptive filtering, a subject of immense practical and theoretical value. The author illustrates extensive commonalities that exist among different classes of adaptive algorithms and even among different filtering theories. He also provides a uniform treatment of the subject matter, addressing some existing limitations, providing additional insights, and detailing extensions of current theory.

The book is designed to be self-contained, with careful attention given to appendices, problems, examples, and a variety of practical computer projects. The bibliography is up-to-date with extensive commentaries on how the contributions relate to each other in time and in context.

Each chapter includes concepts that reinforce the principles covered, bibliographic notes for further study, numerous problems that vary in difficulty and applications, computer projects that illustrate real-life applications, and helpful appendices.

MATLAB® programs that solve all projects are available for download by all readers from the publisher’s Web site at ftp://ftp.wiley.com/public/sci_tech_med/filtering. The computer projects feature topics such as linear and decision-feedback equalization, channel estimation, beamforming, tracking of fading channels, line and acoustic echo cancellation, active noise control, OFDM receivers, CDMA receivers, and even finite-precision effects.

A complete solutions manual for all problems in the book is available to instructors upon request.

To gain insight into this vast and fast-moving field, you need a resource that is logically organized, specific in its presentation of each topic, and far-reaching in scope. Fundamentals of Adaptive Filtering is just that kind of resource.


Product Details

  • Hardcover: 1168 pages
  • Publisher: Wiley-IEEE Press; 1 edition (June 13, 2003)
  • Language: English
  • ISBN-10: 0471461261
  • ISBN-13: 978-0471461265
  • Product Dimensions: 8.4 x 2.5 x 10.1 inches
  • Shipping Weight: 4.9 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (10 customer reviews)
  • Amazon Best Sellers Rank: #1,150,063 in Books (See Top 100 in Books)

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Customer Reviews

10 Reviews
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4 star:
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Average Customer Review
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Most Helpful Customer Reviews

11 of 11 people found the following review helpful:
5.0 out of 5 stars Excellent, March 24, 2004
By A Customer
This review is from: Fundamentals of Adaptive Filtering (Hardcover)
This is the best textbook I've ever read. The mix of theory and practice, examples and math, and the ordered introduction of concepts flows so well it reads like a treasure quest. Everything has its place, and the place is known - you just have to follow the signs and keep an eye out for those which are subtler than others, just to keep things alive and interesting. It's indicative of the clarity of thinking and broad sweep of this work that you would refer to it (I do and other students I know as well), for other subject matter such as communications, linear algebra, digital filters, probability and control theory. The homework problems are not just a series of one-liners as in most graduate level text books, but well-marked road maps addressing points discussed in the text and opening up new possibilities. The computer projects are very well commented and the results analysed. The language is concise yet fluid, and there are extremely few typos of any kind. This is a very, very high quality work.
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10 of 10 people found the following review helpful:
5.0 out of 5 stars Just what I needed, February 4, 2004
By 
Andreas (Lake Mary, FL United States) - See all my reviews
This review is from: Fundamentals of Adaptive Filtering (Hardcover)
I work on 802.11b and 802.11a/OFDM modems and was looking for some kind of coherent text on decision feedback equalization and other tracking schemes when I stumbled upon this book. I'm deep into chapter three and I can already draw the following conclusions.

There are two things that make this book really great.
1) The teaching style. Besides having a wonderful way with words, the author uses plenty of subtle teaching principles that help in the understanding of the material like frequent repetition of the main concepts and slowly building up examples over different sections inside each chapter.

2) Content !!!! Its hard to assimilate abstract material like estimation theory without at the end having some type of useful application or algorithm to show for. The author's examples and computer projects on channel estimation, channel equalization, maximum ratio combining and Rake receivers are very popular building blocks for a variety of modems. It is very motivating to know that after labouring through the chapter the authors feels that you are now ready to understand decision feedback equalizers and so he presents you with a nice DFE computer project.

Difficult topics require competent teaching approaches and that is exactly what you will find in this book.

The only thing that would make this book even better would be a very brief introductory chapter on statistics and linear algebra. So if you are going through the book and you want to quickly revisit the definition of covariance or hermetian transpose there is one centralized section that has all the useful mathematical tools nicely listed.

As a practising engineer, I highly recommend this book.
Andreas S.

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11 of 12 people found the following review helpful:
5.0 out of 5 stars A good book., October 1, 2003
This review is from: Fundamentals of Adaptive Filtering (Hardcover)
For all those of us, working in beamforming or OFDM or equalization or noise control, who find Haykin's writing uninspiring, Sayed's work has all the elegance of Prof Kailath's pedagogical style. This is one scrumptious intellectual meal. Every extant variation of the LMS and RLS algorithms is detailed, and some histroical context provided. The mathematical background needed or assumed is rudimentary. The Matlab projects are extensive in scope - yet, like most Matlab sources, they will take work in understanding their nuances.
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Inside This Book (learn more)
First Sentence:
In this first chapter we focus on the basic, yet fundamental, problem of estimating an unobservable quantity from a collection of measurements in the least-mean-squares sense. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
block adaptive filters, lower triangularizes, subband adaptive filters, regressor sequence, affine projection algorithms, adaptive filter update, normalized lattice filter, regressor covariance matrix, estimated computational cost, other adaptive filters, resulting residual vector, successive regressors, regularized projection, whose eigenvalue spread, adaptive channel estimation, assuming real data, nonlinear decision device, white input data, adaptive filtering literature, different adaptive filters, sufficiently small degree, quantized environments, fullband filter, one real division, variance relation
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Bibliographic Notes, Summary of Main Results, Step-size Figure, Fundamental Variance Relation, Fundamental Energy-Conservation Relation, Priori Error-Feedback Lattice Filter, Correlated Gaussian, Iteration Normalized, Significance of Data Structure, Estimation Given Dependent Observations, Posteriori Error-Feedback Lattice Filter, Time Figure, Design Examples, Iteration Array, Nonstationary Data Model, Priori-Based Robust Filters, General Time-Update Result, Minimum-Variance Unbiased Estimation, More Constrained, Regularized Projection Problems, Use Price, Algorithm Recursion, Causal Wiener-Hopf Filtering, Iteration Trajectory, Problem Cost
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