The Chaotic Neural Network Hysteresis Synchronization Control Research

Chaotic system is a complex nonlinear motion system, which contains evolution ofnon equilibrium process on the initial conditions extremely sensitive. Chaos phenomenondetermines the dynamic performance without specific law attribute, as a rom naturalphenomenon. Under certain conditions, the system of nonlinear factors the initialcondition of the sensitivity of system performance of a kind of movement form, namelychaos phenomenon. Along with the people to the chaos phenomenon of research,scientific domain appeared chaos learn this subject. In this paper, the main research resultsare as follows:Firstly, the basic theory method of chaos gives a comprehensive study analysis,focusing on the chaos neural network problems are more in-depth study, especially forchaotic neural network adaptive lag, with pulse chaotic neural network to the lag of theproblems in the specific research analysis, the corresponding mathematical model wasestablished, gives the chaos neural network adaptive hysteresis synchronous controlalgorithm the pulse chaotic neural network adaptive synchronization hysteresis controlalgorithm, constructed the corresponding Lyapunov function is realized with neuralnetwork to carry on the hysteresis synchronous control.Secondly, study analysis of the chaotic neural network for a class of (Lorenzsystem, Lv system, Chen system) chaotic system synchronization control problem, thispaper presents the chaos neural network to the nonlinear chaos system hysteresissynchronous control algorithm. Lyapunov stability theory applied to the above methodsfor the theory, it is proved that the results show that the method is correct, this method canbe extended to other isomerism chaos system synchronization problem.Finally, the numerical simulations verify the effectiveness of these methods.