Multi-Variable Input Backpropagation Neural Network Algorithm
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Resource Overview
MATLAB implementation of a backpropagation neural network algorithm supporting multi-variable inputs, featuring four-dimensional input processing with one-dimensional output
Detailed Documentation
In this project, I implemented a multi-variable input backpropagation neural network algorithm using MATLAB. To handle complex input patterns, the network architecture was designed with four-dimensional input processing while maintaining one-dimensional output. The implementation utilizes MATLAB's Neural Network Toolbox functions including 'feedforwardnet' for network creation and 'train' for backpropagation training with gradient descent optimization. Key parameters such as learning rate, number of hidden layers, and activation functions were configured to ensure efficient convergence during the training phase.
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