Input-to-State stability analysis for memristive Cohen-Grossberg-type neural networks with variable time delays

Abstract In this paper, we discussed the input-to-state stability of a class of memristive Cohen–Grossberg-type neural networks with variable time delays. Based on a nonsmooth analysis and set-valued maps, some novel sufficient conditions are obtained for the input-to-state stability of such networks, which include some known results as particular cases. Especially, when the input is zero, it reduced to asymptotical stability of the state. Finally, an illustrative example is presented to illustrate the feasibility and effectiveness of our results.

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