MATLAB Implementation of Wavelet Neural Networks

In this article, I would like to share MATLAB code implementations for wavelet neural networks. The code includes essential functions for constructing and training wavelet neural networks, featuring wavelet transform integration with neural network architectures. Readers are encouraged to carefully examine the implementation details, which demonstrate key algorithms such as wavelet coefficient initialization, network training optimization, and signal processing applications. Before utilizing this code, it's recommended to familiarize yourself with fundamental concepts of wavelet neural networks, including wavelet theory basics and neural network principles. This implementation provides practical examples of how wavelet transforms can be combined with neural networks for enhanced pattern recognition and time-series analysis capabilities. The shared code serves as a valuable resource for learning and exploring wavelet neural network applications in various problem domains.