自适应和自学习系统的原则（The Principles of Adaptive Filters and Self-learning Systems）

Principles of Adaptive Filters and Self-learning Systems Publisher: Springer | Pages: 386 | 2005-07-22 | ISBN: 1852339845 | PDF | 3 MB 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.