Neural network identification of a nonlinear circuitmodel of hysteresis

Abstract

A nonlinear circuit model of hysteretic phenomena is presented. The model provides a close prediction of static hysteresis and exhibits realistic dynamic features. The parameters of the circuit model can be identified by proper neural network training. Basic features and results are discussed.