On The Control And Synchronization Of A Class Chaotic Time-delayed Neural Networks

Since someone proposed some questions of cellular neural networks in1943, neuralnetwork became a popular research topic in the fled of application and rapid develop-ment in recent decades. There have a variety of neural network, such as Hopfled neuralnetwork, celluar networks and Cohn-Grossberg neural network and so on. Including with-out delay, with the delay, discrete delay, distributed delays and Bidirectional associativememory(BAM), etc. In1990, Louis M.Pecora and Thomas L.Carroll and others havestudied the synchronization problem of chaotic system in the literature, The next decadeas the neural network synchronization of many experts and scholars research hot topic.Chaos synchronization control its has broad application prospects, such as confdentialcommunication, image processing, pattern recognition, attracted the attention of a con-siderable number of experts and scholar. In this paper, by using diferent control methods,designing diferent synchronous controller, researched on generalized projective synchro-nization of three categories chaotic cellular neural networks with diferent delay. Themain contents in this paper can be summarized as follows:The frst section is introduction, in which we present research background, purposeand signifcance of neural network control and synchronization of chaotic systems, andthere are give the research status and results of neural network control and synchronizationof chaotic systems. Finally the organization of this paper is also presented.In Section2, With mixed generalized projective synchronization of a class of linearneural network is discussed. A class of mixed time-delay neural network was establishedby the chaotic model, through the design of linear controller, it is obtained by this kind ofmixing time delay neural network, and the sufcient conditions for generalized projectivesynchronization. Some numerical examples and simulations are presented to show thefeasibility and efectiveness of the proposed methods.In Section3, Research and discuss the method based on nonlinear observer with mixed generalized projective synchronization of chaotic neural network with time delay. Designthe appropriate observer through the linear system theory knowledge, and by using poleassignment, Get the rule of the generalized projective synchronization of chaotic neuralnetwork system. Some numerical simulations are presented to verify the obtained results.In Section4, we discussed a class of stochastic linear generalized projective synchro-nization of chaotic neural network with noise disturbance, and it is diferent from theprevious two chapters in this chapter, we give the projection function rather than theproportional coefcient. By using Lyapunov stability theory and robust control method,make the controller in the system by the noise disturbance situation, it also can ensurethe accuracy of the error of the system in a certain converge to the small area near theorigin. Through the numerical simulation to verify the conclusion.