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.