Dynamic Analysis Of Neutral-type Memristive Neural Network Systems

In this paper,the dynamical properties of neutral-type memristive neural network systems are studied by using stochastic analysis theory,linear matrix inequalities and Lyapunov functional methods.Firstly,the adaptive synchronization of a kind of mixed delays neutral-type memristive neural network systems with different controllers is investigated.By establishing appropriate Lyapunov functions and linear matrix inequalities,it is proved that the conditions of adaptive synchronization of the system and some important relevant conclusions are obtained,besides numerical example and the results of Matlab drawing are given to verify the effectiveness of the conclusions.Secondly,the stability of a kind of neutral-type memristive neural networks is discussed.In the model,random disturbance and mixed delay are considered simultaneously,which make the model is more abundant.The conditions of the mean-square exponential input-to-stability for system are obtained by using the stochastic analysis theory and Lyapunov functional.Furthermore,numerical example and the results of Matlab drawing are given to illustrate the correctness of the conclusions.