Adaptive almost sure asymptotically stability for neutral-type neural networks with stochastic perturbation and Markovian switching

The problem of stability via adaptive controller is considered for time-delay neutral-type neural networks with stochastic noise and Markovian switching in this paper. A new criterion of almost sure (a.s.) asymptotic stability for a general neutral-type stochastic differential equation is proposed. Based on this criterion, and by using of the generalized Ito?s formula and the M-matrix method, a delay dependent sufficient condition is established to ensure the almost sure asymptotic stability for neutral-type neural networks with stochastic perturbation and Markovian switching. Meanwhile, the update law of the feedback control is determined. A numerical example is provided to verify the usefulness of the criterion proposed in this paper.

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