Time-Variation Nonlinear System Identification Based on Bayesian-Gaussian Neural Network

摘要

A Bayesian-Gaussian neural network (BGNN) method for nonlinear time variation system identification is proposed in this article. In the redefined BGNN training algorithms, the threshold matrix parameters are optimized by the swarm intelligence optimization algorithm(s) off-line and the sliding window data method are adopted for the BGNN on-line prediction. Some typical time-variation nonlinear systems are been used for the validation of the BGNN modeling effectiveness.