Synchronization of master-slave memristive neural networks via fuzzy output-based adaptive strategy

Abstract

This paper considers the synchronization problem of memristive neural networks (MNNs) via a fuzzy output-based adaptive strategy, where the fuzzy model of MNNs with state-dependent memristor is employed. Several adaptive rules for the controller gain of the slave NNs and its connection weights are designed, which provide a new way to realize the state synchronization between master and slaver memristive NNs. Under these adaptive update rules, several synchronization results and their performance analysis are given, which verified by a simulation example.