Multistability analysis for a general class of delayed CohenGrossberg neural networks ?
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 CohenGrossberg 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.
multistability analysis cohengrossberg neural networks periodic orbit exponential stability equilibrium