Wavelet Neural Network Based on BP Network

A wavelet neural network program based on BP network architecture, implemented using MATLAB. This program can handle various data processing and pattern recognition tasks by combining the advantages of wavelet transformation with neural network learning capabilities, providing a robust and flexible analytical tool. The implementation leverages MATLAB's neural network toolbox for backpropagation optimization while incorporating wavelet decomposition functions for feature extraction. Key algorithm components include wavelet coefficient computation, weight adjustment through gradient descent, and activation function customization. Applicable to signal processing, image analysis, speech recognition, and other domains, the program supports customization and extension based on specific requirements. It features an intuitive user interface and comprehensive functionality, enabling users to efficiently conduct experiments and analytical studies. Whether for academic research or engineering applications, this wavelet neural network program offers reliable support with configurable parameters for wavelet types, network layers, and training epochs.