Principles of Adaptive Filters and Self-learning Systems (Advanced Textbooks in Control and Signal Processing) [Paperback]

Anthony Zaknich (Author)

Book Description

Series: Advanced Textbooks in Control and Signal Processing | Publication Date: July 22, 2005

Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems

Editorial Reviews

Review

From the reviews: "An excellent tutorial for graduate students and a comprehensive introduction for researchers working in adaptive systems. Summing Up: Highly Recommended." (J. Y. Cheung, Choice, February, 2006)

From the Back Cover

Kalman and Wiener Filters, Neural Networks, Genetic Algorithms and Fuzzy Logic Systems Together in One Text Book How can a signal be processed for which there are few or no a priori data? Professor Zaknich provides an ideal textbook for one-semester introductory graduate or senior undergraduate courses in adaptive and self-learning systems for signal processing applications. Important topics are introduced and discussed sufficiently to give the reader adequate background for confident further investigation. The material is presented in a progression from a short introduction to adaptive systems through modelling, classical filters and spectral analysis to adaptive control theory, nonclassical adaptive systems and applications.   Features: • Comprehensive review of linear and stochastic theory. • Design guide for practical application of the least squares estimation method and Kalman filters. • Study of classical adaptive systems together with neural networks, genetic algorithms and fuzzy logic systems and their combination to deal with such complex problems as underwater acoustic signal processing. • Tutorial problems and exercises which identify the significant points and demonstrate the practical relevance of the theory. • PDF Solutions Manual, available to tutors from springeronline.com, containing not just answers to the tutorial problems but also course outlines, sample examination material and project assignments to help in developing a teaching programme and to give ideas for practical investigations.

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Product Details

• Paperback: 408 pages
• Publisher: Springer; 1st Edition. edition (July 22, 2005)
• Language: English
• ISBN-10: 1852339845
• ISBN-13: 978-1852339845
• Product Dimensions: 9.1 x 6.1 x 0.8 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #2,481,225 in Books (See Top 100 in Books)
  • #61 in Books > Computers & Technology > Programming > Algorithms > Genetic

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Customer Reviews

Most Helpful Customer Reviews

1 of 4 people found the following review helpful:

5.0 out of 5 stars but not for my immediate needs, November 3, 2007

By 

Norman Hines "geek nerd" (California) - See all my reviews
(REAL NAME)   

This review is from: Principles of Adaptive Filters and Self-learning Systems (Advanced Textbooks in Control and Signal Processing) (Paperback)

This is a good book, but my immediate need is for a much more introductory book. I'm just through the first chapter and have already encountered ideas and concepts I've never heard before, and my undergraduate major was mathematics! What's the textbook(s) for the prerequisite(s) for the class that would use "Principles..."?