Fuzzy Neural Networks for Function Approximation and Classification
Fuzzy neural network approximation and classification, fuzzy rule extraction, fast-growing and pruning network algorithms
RBF Neural Network for Nonlinear System Approximation
Successful implementation of RBF neural network for approximating nonlinear systems, with discussions on current limitations and areas for improvement. Implementation includes radial basis function centers selection, weight optimization, and network training algorithms.
Gradient-Based RBF Neural Network Implementation
An RBF neural network program implemented using gradient descent method, designed for approximating and fitting input data patterns with optimization capabilities.
CMAC Network Approximation for Nonlinear Systems
A program demonstrating CMAC (Cerebellar Model Articulation Controller) network approximation for nonlinear systems, featuring implementation details with code examples and algorithmic explanations. This reference implementation covers memory-based learning mechanisms and mapping techniques suitable for control applications.