Traditionally, neural networks and wavelet theory have been two separate disciplines, taught separately and practiced separately. Foundations of Wavelet Networks and Applications unites these two fields to provide a comprehensive, integrated presentation of wavelets and neural networks that forms a self-contained treatment of wavelet networks. Requiring minimal prerequisites, it focuses on establishing insight and understanding rather than rigorous mathematical foundations. It prepares and inspires readers not only to help ensure that the potential of wavelet networks is achieved, but also to open new frontiers in research and applications. Each chapter includes exercises.
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