LMI-Based Lagrange Stability of CGNNs with General Activation Functions and Mixed Delays

Abstract

This paper deals with the problem on Lagrange stability of Cohen-Grossberg neural networks (CGNNs) with both mixed time delays and general activation functions. By virtue of Lyapunov functional and Halanay delay differential inequality, several criteria in linear matrix inequality form for Lagrange stability of CGNNs are obtained. Meanwhile, the limitation on the activation functions being bounded, monotonous and differentiable is released and detailed estimation of the globally exponentially attractive sets are also given out. Finally, concluding remark is given.