New mean square exponential stability condition of stochastic fuzzy neural networks

This paper investigates the stability problem for interval type-2 (IT2) stochastic fuzzy neural networks. Firstly, an IT2 stochastic fuzzy neural network is constructed. Secondly, by using stochastic analysis approach and Itô׳s differential formula, a new sufficient condition ensuring mean square exponential stability is obtained. The condition can be expressed in terms of convex optimization problem. The main contribution of this paper is that the IT2 stochastic fuzzy neural network with parameter uncertainties is first proposed. The parameter uncertainties are bounded, and can be effectively expressed by upper and lower membership functions. Two numerical examples are proposed to show the effectiveness of the proposed scheme.