Stability Analysis Of Fuzzy Cellular Neural Network With Markov Jumping Parameters

The fuzzy neural network is widely used in real life, such as pattern recognition, image processing and other aspects. Impulse control neural network research results are also have played a very important role in mechanical movement, space technology in the real life. Delay phenomenon in vehicle manufacturing, building structure, financial engineering, information and conununications, biotechnology and brain information science and many other real-life technology also has a very wide range of applications. Hence, Neural Networks stability has great significance not only in theory, the application also has a very important meaning and value. In this paper, global asymptotic stability of the fuzzy cellular neural networks with Markov jumping parameters and leakage-delays were studied, and achieved good results. The main contents are as follows:The first chapter is an introduction, describes the proposed and significance of Fuzzy Cellular Neural Networks and its stability, the theory of the stability of fuzzy cellular neural networks studied in this paper and the stability of dynamical systems, and finally a brief introduction for the main work this article made.The second chapter, Applicate the theory of Lyapunov function.combined with some of the methods of the liberty matrix and linear matrix inequalities, made a further study of the stability of fuzzy cellular neural networks with Markov jumping parameters and leakage-delays. Through construct a new Lyapunov-krasovkii functional,proposed a sufficient condition of this kind of fuzzy celluiar neural networks with global asymptotic stability, and then through the MATLAB numerical simulation to verify the feasibility and correctness of the conclusion.