Robust exponential stability of interval Cohen–Grossberg neural networks with time-varying delays

Abstract

In this paper, the problem of robust exponential stability for a class of interval Cohen–Grossberg neural networks with time-varying delays is investigated. Without assuming the boundedness and differentiability of the activation functions and any symmetry of interconnection matrices, some sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point are derived. Some comparisons between the results presented in this paper and the previous results admit that our results are the improvement and extension of the existed ones. The validity and performance of the new results are further illustrated by two simulation examples.