Multiple ψ-Type Stability of Cohen-Grossberg Neural Networks With Unbounded Time-Varying Delays

This paper investigates Cohen-Grossberg neural networks (CGNNs) with unbounded time-varying delays. The existence condition of multiple equilibrium points is established by the algebraic inequality method. And then, the phi-type stability is studied by analysis method for CGNNs with unbounded time-varying delays, and the relative convergence rate can be adjusted by the selection of phi-type functions. Moreover, by introducing the topological degree, the algebraic sum of the number of equilibria remains unchanged for any smooth function in the specified metric space. Finally, one numerical example is implemented to show the validity of the presented results.

Automated summary

This paper investigates the existence condition of multiple equilibrium points in Cohen-Grossberg neural networks with unbounded time-varying delays using the algebraic inequality method. It also studies phi-type stability and the adjustment of relative convergence rate by selecting phi-type functions for CGNNs with unbounded time-varying delays. Furthermore, the introduction of topological degree ensures that the algebraic sum of equilibria remains unchanged for any smooth function in the specified metric space.