Novel stability condition of stochastic fuzzy neural networks with Markovian jumping under impulsive perturbations

For the first time, this paper investigates the global asymptotic stability of stochastic fuzzy neural networks with mixed delays and Markovian jumping under impulsive perturbations in mean square. The mixed delays include time-varying delay and continuously distributed delay. By using stochastic analysis method, linear convex combination technique, Jensen integral inequality and the free-weight matrix method, a novel sufficient condition is derived to ensure the global asymptotic stability of the equilibrium point of the considered networks in mean square. The proposed result, which is expressed in terms of linear matrix inequalities, can be easily checked via Matlab software. Finally, a numerical example is given to demonstrate the effectiveness and less conservativeness of our theoretical results over existing literature.