Study On Global Exponential Stability Of Two Neural Network Models

In the past30years, the research of Hop field neural network model has been developed rapidly. The model has been widely used in the fields of medicine, biology, computer science, economics, automatic control and etc., which makes it more significant. In the research of the neural network model, the study of the stability is the key part. The general method is to construct different Lyapunov functional, then use different inequalities to analyze the discriminant of stability. The commonly used inequalities are linear matrixine qualities (LMI), the coefficient matrix norm inequalities as well as Hanalay differential inequality and so on.This thesis will mainly introduce the applications of Gronwall inequality in differential equations and its stability. Mainly use the Gronwall inequality to study the stability of the delayed Hopfieldneural network model. Based on this approach, this thesis studies the stability of the discrete delay neural network model.