Abstract
The problem of global robust exponential stability is investigated for Fuzzy stochastic uncertain discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (T-S) fuzzy models. The uncertainties are assumed to be the linear fractional form. Based on Lyapunov-Krasovskii functional (LKF) method in combination with a finite sum inequality, a delay-dependent exponential stability criterion is established in terms of linear matrix inequalities (LMIs). A numerical example is provided to show the effectiveness of the proposed method.
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