New Results on the Exponential Stability of Class Neural Networks with Time-Varying Lags

Abstract

In this article, some novel approaches to the analysis of global exponential stability (GES) for a class of neural networks with time-varying lags are presented. For functional differential equations, these approaches to are based on Lyapunov stability theory. Then, the necessary and sufficient conditions for GES of the equation considered have been discussed. An example was given to illustrate the qualitative behavior of the solution of the proposed equation and MATLAB-Simulink Program was used to demonstrate the validity of the results obtained in this sample. Consequently, the obtained results include and improve the results found in the related literature.