Equilibria and Stability Analysis of Cohen-Grossberg BAM Neural Networks on Time Scale

doi:10.1007/s11424-022-0250-5

This paper considers the Cohen-Grossberg BAM neural networks (CG-BAMNNs) on time scale, which can unify and generalize the continuous and discrete systems. First, the criteria for the existence and uniqueness of the equilibrium of CG-BAMNNs are derived on time scale. Then based on that, the authors give the criteria for the stability and estimation of equilibrium of the CG-BAMNNs on time scale. The method proposed in this paper unifies and generalizes the continuous and discrete CGBAMNNs systems, and is applicable to some other neural network systems on time scale with practical meaning. The effectiveness of the proposed criteria for delayed CG-BAMNNs is demonstrated by numerical simulation.

Key words: Cohen-Grossberg BAM neural networks, existence, numerical simulation, stability, uniqueness

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