Three MATLAB Radial Basis Function Neural Network Programs: Cluster-Based, Gradient-Based, and OLS-Based Implementations

Three MATLAB implementations of Radial Basis Function (RBF) neural networks featuring distinct training methodologies: cluster-based RBF, gradient descent-based RBF, and Orthogonal Least Squares (OLS)-based RBF networks with detailed algorithmic descriptions and code structure explanations.

MATLAB Implementation of RBF Learning Methods

RBF learning methodologies encompassing: k-means clustering, gradient descent optimization, and OLS (Ordinary Least Squares) algorithms with practical implementation approaches.

Seven RBF Neural Networks: Source Code Collection with Implementation Approaches

Source code implementations for seven RBF neural networks featuring gradient-based methods, OLS (Ordinary Least Squares), clustering algorithms, k-means clustering, and function approximation techniques for network design and predictive modeling