The Stability Analysis Of Several Kinds Of Neural Networks

In recent years, the dynamical issues of delayed neural networks have attracted worldwide attention. Many interesting stability criteria for the equilibrium solutions of delayed neural networks have been obtained, such as the global asymptotic stability, global exponential stability etc. In this paper, several sufficient conditions are derived for the global stability of the equilibriums solutions of generalized neural networks by employing Lyapunov stability theorem and the technique of differential inequalities.According to the stability theory of functional differential equations, by employing proper Lyapunov functional, we obtain some sufficient conditions for the global asymptotic stability of the equilibrium solution. By use of LMI technique, the sufficient conditions for the global exponential stability of the solution are derived. The stability criteria for the solution of the generalized neural networks with distributed delay was studied according to the method of of Lyapunov functional and the technique of inequality analysis. By employing some different inequalities such as Young inequality and Hanalay type inequality , we get some sufficient conditions of the global exponential stability of the equilibrium solution of neural networks with distributed delays. The results obtained in this paper are more accurate than the ones reported in the literature and more convenient in practice .