Parameterization Of Wavelets And Research On Wavelet Neural Networks

In recent years,the research in the field of wavelets analysis has focused on Multiwavelets and Nonseparable wavelets. Symmetry,Orthogonality,Vanishing moment,Balacing and finite supported are the properties concerned widely of the wavelets theory and their applied research.It is significant for the application of wavelts to parameterize them and construct a class of function banks of Multiwavelets and Nonseparable wavelets which could supply the most optimized bases of wavelets based on the different applied object and the different applied demands.The Wavelets Neural Network is the novel and efficient model of nonlinear signal processing developed in latest years. Optimized wavelet networks adaptively according to the handled question could offer the scientific guide of model design and the systemic theoretic guarantee.This project intends to construct a parameterized function banks about the internal properties of wavelets aimed at a extensive kind of Multi-wavelets and some categories of relatively specific Non-separable wavelets with significant practical background, and disclose the essential characters of Non-separable wavelets. Through optimizing the bases of wavelets, it will build a problems oriented system of self-adaptive Wavelets Neural Network and apply it to the relative problems of signal processing.