MATLAB Radial Basis Function Neural Network Source Code

This MATLAB-based source code implements a Radial Basis Function Neural Network (RBFNN), designed for advanced data analysis and pattern recognition applications. The implementation utilizes MATLAB programming language to simulate neuron connections and information transmission through radial basis functions. The core algorithm features Gaussian radial basis functions for hidden layer activation and linear output layers for final predictions. The source code includes key functions for network initialization, training using methods like orthogonal least squares learning, and prediction capabilities. It supports adjustable parameters such as spread constants, number of hidden neurons, and training epochs for optimal performance. The implementation handles data preprocessing, normalization, and validation set evaluation. This robust implementation serves various applications including image recognition, speech processing, and predictive analytics. It provides a flexible and reliable approach for handling complex datasets while delivering accurate results and predictions. The code structure supports both academic research and engineering applications, featuring modular design with clear function documentation, making it a powerful and practical tool for neural network implementations.