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On the Dynamical Behaviors of Neural Networks System on Time Scales

Author: ZhangHao
Tutor: JiangHaiJun
School: Xinjiang University
Course: Operational Research and Cybernetics
Keywords: Lyapunov function Time scale BAM neural networks Higher Order Cohen-Grossberg neural networks Pulse control Anti- periodic solutions Globally exponentially stable
CLC: N941.3
Type: Master's thesis
Year: 2010
Downloads: 58
Quote: 0
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Abstract


The time scale theory and neural network combined with the kinetic properties of the new areas , the mathematical description of discrete and continuous mixing process to achieve continuous model and the discrete model accurately portrayed and the specific implementation of the method of mathematical system is a very optimized . unified study is very significant paper through the use of time -scale theory , respectively, on the time scale exponential stability of BAM neural networks with impulse control , exponential stability of periodic solution of BAM neural network on the time scale of the pulse control the main content of this article can be summarized as follows : an Introduction , pulse and pulse control neural network research background , purpose and significance , given the status and results of the pulse on the time scale of the neural network control Finally, the organizational structure of this article . 2 introduces a pulse BAM neural network control system on the time scale . 3 discussion on the time scale pulse BAM neural network control system exponentially stable first time scale based on the theory , through the design of linear pulse controller and Lyapunov function to obtain a sufficient condition to guarantee the exponential stability of BAM neural networks . then verify the feasibility and effectiveness of the method through some numerical examples and simulation . section solution for BAM neural networks with impulse control cycle time scale the exponentially stable discussed . , through the design of linear pulse controller and Lyapunov function on the basis of the theory of time scales , resulting in exponential stability of the guarantee system new sufficient condition , and numerical simulation to verify the conclusion . discussed briefly five stable solution for the higher order Cohen-Grossberg neural network system counter-cyclical index system exponentially stable sufficient condition for these results are new and algebraic methods to verify the validity of the conclusions .

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CLC: > SCIENCE AND > Journal of Systems Science > Systems,modern systems theory > System Dynamics
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