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  • Title: Stability analysis of time-delay neural networks subject to stochastic perturbations.
    Author: Chen Y, Zheng WX.
    Journal: IEEE Trans Cybern; 2013 Dec; 43(6):2122-34. PubMed ID: 23757521.
    Abstract:
    This paper is concerned with the problem of mean-square exponential stability of uncertain neural networks with time-varying delay and stochastic perturbation. Both linear and nonlinear stochastic perturbations are considered. The main features of this paper are twofold: 1) Based on generalized Finsler lemma, some improved delay-dependent stability criteria are established, which are more efficient than the existing ones in terms of less conservatism and lower computational complexity; and 2) when the nonlinear stochastic perturbation acting on the system satisfies a class of Lipschitz linear growth conditions, the restrictive condition P < δI (or the similar ones) in the existing results can be relaxed under some assumptions. The usefulness of the proposed method is demonstrated by illustrative examples.
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