pt. I. Introduction to Wavelet Theory -- pt. II. Preprocessing: The Multiresolution Approach -- pt. III. Spline-Based Wavelets Approximation and Compression Algorithms -- pt. IV. Automatic Generation of a Fuzzy System with Wavelet Based Methods -- pt. V. On-Line Learning -- pt. VI. Nonparametric Wavelet-Based Estimation and Regression Techniques -- pt. VII. Developing Intelligent Products -- pt. VIII. Genetic Algorithms and Multiresolution -- Annexes Lifting scheme, nonlinear wavelets.

This book presents the state of integration of wavelet theory and multiresolution analysis into soft computing. It is the first book on hybrid methods combining wavelet analysis with fuzzy logic, neural networks or genetic algorithms. Much attention is given to new approaches (fuzzy-wavelet) that permit one to develop, using wavelet techniques, linguistically interpretable fuzzy systems from data. The book also introduces the reader to wavelet-based genetic algorithms and multiresolution search. A special place is given to methods that have been implemented in real world applications, particularly the different techniques combining fuzzy logic or neural networks with wavelet theory.