On The Exponential Synchronization Behaviors For Fuzzy Cellular Neural Networks With Time Delays And Impulsive Effects

Fuzzy cellular neural networks synchronization have enormous potential in wide va-rieties of applications, many specialists and scholars apply themselves to the research ofthe theory and achieve many perfect productions. In this paper, the globally exponentialsynchronization of delayed fuzzy cellular neural networks with impulsive efects and timedelays are concerned. The main contents of this paper include: exponential synchroniza-tion for fuzzy cellular neural networks with time-varying delays and impulsive efects,and exponential lag synchronization of delayed fuzzy cellular neural networks with linearimpulses, exponential synchronization for coupled identical Yang-Yang type fuzzy cellularneural networks with time-varying delays, respectively.The main contents in this paper can be summarized as follows:1. Firstly, in the frst section of the frst chapter, we induction the development pro-cess of fuzzy cellular neural networks. In subsection2, induction the research signifcanceof fuzzy cellular neural networks. In section3, we induction the research results of fuzzycellular neural synchronization with impulsive efects and time delays. In section4, theresearch contents of this paper.2. In the second chapter, we investigate the exponential synchronization for fuzzycellular neural networks with time-varying delays and nonlinear impulsive efects. By uti-lizing inequality techniques and Lyapunov functional methods, some sufcient conditionson the exponential synchronization are obtained based on p-norm. Finally, an examplewith numerical simulations is presented to show the feasibility and efectiveness of theproposed methods.3. In the third chapter, a class of fuzzy cellular neural networks with impulsive efectsand lag delayed exponential synchronization is discussed. By the Lyapunov-Lasall princi-ple of functional diferential equations. Some sufcient conditions on the impulsive efectsexponential lag synchronization of the FCNNs are obtained using inequality methods. Finally, an example is presented to show the feasibility and efectiveness of the proposedmethods.4. In the forth chapter, a class of coupled identical Yang-Yang type fuzzy cellularneural networks with time-varying delays is discussed. Based on the simple adaptivecontroller, a set of sufcient conditions are developed to guarantee the synchronizationof the coupled Yang-Yang type fuzzy cellular neural networks with time-varying delays.By the invariance principle of functional diferential equations, constructing a generalLyapunov-Krasovskii functional and employing a linear matrix inequality, some sufcientconditions on the Yang-Yang type fuzzy cellular neural networks are obtained. Finally, annumerical example is presented to show the feasibility and efectiveness of the proposedmethods.