Wavelet Neural Network Source Code Implementation

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Resource Overview

This is a wavelet neural network source code implementation featuring forward propagation computation, serving as an educational foundation for understanding neural network principles and wavelet transformations.

Detailed Documentation

Here, I would like to share a source code implementation of a wavelet neural network. While it may not represent the most optimized version, I believe it holds value for those interested in neural networks. Furthermore, by analyzing this code, we can gain deeper insights into the working mechanisms of wavelet neural networks. Specifically, this implementation demonstrates the forward propagation process of the neural network, computing outputs for given input data. The code structure allows for straightforward modification to incorporate backpropagation algorithms for parameter optimization. Key components include wavelet activation functions, weight initialization methods, and layer-to-layer data transmission logic. This program serves as an excellent learning tool that helps bridge theoretical understanding of neural networks and wavelet transforms with practical implementation techniques.

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