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Multistability analysis for a general class of delayed Cohen-Grossberg neural networks. (English) Zbl 1256.93086
Summary: In this paper, by discussing parameter conditions based on properties of activation functions, we decompose state space into positively invariant sets and establish sufficient conditions for the existence of locally stable equilibria for delayed Cohen-Grossberg Neural Networks (CGNNs) through Cauchy convergence principle. Some new criteria are derived for ensuring equilibria (periodic orbits) to be locally or globally exponentially stable in any designated region. Finally, our results are demonstrated by four numerical simulations.
MSC:
93D20Asymptotic stability of control systems
92B20General theory of neural networks (mathematical biology)
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