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Principles of Adaptive Filters and Self-Learning Systems by A. Zaknich
How can a signal be processed for which there are few or no a priori data? This text covers Kalman and Wiener filters, neural networks, genetic algorithms and fuzzy logic systems together in a unified treatment. It is useful for one-semester introductory graduate or senior undergraduate courses.This is an ideal textbook for one-semester introductory graduate or senior undergraduate courses in adaptive and self-learning systems for signal processing. The material progresses 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 deals with complex problems like underwater acoustic signal processing.- Tutorial problems and exercises which identify significant points and demonstrate the practical relevance of the theory.- PDF Solutions Manual available to tutors containing answers to the tutorial problems, course outlines, sample examination material and project assignments. |
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| Author(s) : A. Zaknich | Format : Paperback Book |
| ISBN-10 : 1852339845 | ISBN-13 : 9781852339845 |
| RRP : £35.00 | Best available price : £ / $ |
| Prices as of : BST check live prices | |
Product Details:
Series Title : Advanced Textbooks in Control & Signal Processing
Country Publication : United Kingdom
Publication Date : 01/04/2005
Publisher : Springer-Verlag London Ltd
Page Length : XXII, 386mm
Page Size : 235mm