The problem of stochastic robust stability for Markovian jump discrete-time delayed neural networks with multiplicative nonlinear perturbation is investigated via Lyapunov stability theory in this paper. Based on the linear matrix inequality (LMI) methodology, a novel analysis approach is developed. The sufficient conditions of stochastically robust stable are given in terms of coupled linear matrix inequalities. The stable criteria represented in LMI setting are less conservative and more computationally efficient than the methods reported in the literature. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Xie, L., Liu, T., Lu, G., Liu, J., & Wong, S. T. C. (2006). Stochastic robust stability analysis for Markovian jump discrete-time delayed neural networks with multiplicative nonlinear perturbations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3971 LNCS, pp. 172–178). Springer Verlag. https://doi.org/10.1007/11759966_26
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