Mode and Delay-dependent Stochastic Stability Conditions of Fuzzy Neural Networks with Markovian Jump Parameters

Abstract

This paper investigates the stochastic stability of fuzzy Markovian jumping neural networks with time-varying delay and continuously distributed delay in mean square. By using the reciprocal convex combination approach, Jensen and Jensen-type integral inequality, linear convex combination technique and the free-weight matrix method, several novel mode and delay-dependent sufficient conditions are derived to ensure the stochastic stability of the equilibrium point of the considered networks in mean square. The proposed results can be easily checked via Matlab software. Finally, two numerical examples are given to demonstrate the effectiveness and less conservativeness of our theoretical results over existing literature.