Robust exponential stability of a class of uncertain stochastic fuzzy BAM neural networks with mixed delays

This paper is concerned with the problem of mean square exponential stability for a class of stochastic fuzzy bidirectional associative memory (BAM) neural networks with mixed delays. The discrete delays are assumed to belong to an interval and uncertainties considered to be the linear fractional forms. By using Lyapunov-Krasovskii functional (LKF) method and employing some new analysis approaches, several delay-range-dependent exponential stability criteria are established in terms of linear matrix inequalities (LMIs). The decay rate can be freely selected without any constraints and the differential of delays be any finite values in derived criteria. Two numerical examples are presented to show the validness of the proposed results.