An Analysis of Global Stability of Takagi-Sugeno Fuzzy Cohen-Grossberg Neural Networks with Time Delays

Abstract

This paper deals with the problem of the global asymptotic stability of Takagi-Sugeno (T-S) fuzzy Cohen-Grossberg neural networks with multiple time delays. By using Lyapunov method and some basic properties of matrices, and employing the nondecreasing and slope-bounded activation functions, an easily verifiable sufficient criterion is derived to establish the asymptotic stability of a general class of (T-S) fuzzy Cohen-Grossberg neural networks with multiple time delays. The obtained stability condition establishes some relationships between the network parameters of the neural network model independently of the delay parameters. A numerical example is also given to illustrate the effectiveness of the theoretical results.