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Some Research On Chaotic Synchronization Analysis Of Neural Networks With Markovian Jumping

Posted on:2016-03-30Degree:MasterType:Thesis
Country:ChinaCandidate:Q Q LvFull Text:PDF
GTID:2308330470974554Subject:Mathematics
Abstract/Summary:PDF Full Text Request
This article focuses on the Synchronization of a class of discrete-time neural networks with Markovian Jump and a class of stochastic synchronization of neutral-type chaotic Markovian neural networks with impulsive effects Based on the Lyapunov-Krasovskii functional,drive-response concept and time-delay feedback control techniques, obtained the conditions for the stochastic synchronization.Chapter 1 is an introduction, mainly on the proposed chaotic neural network and the meaning of control and synchronization, the stochastic synchronization of two identical Markovian jumping chaotic delayed neural networks, the stability theory of dynamical systems, and describes the main work of this paper.Chapter 2, the adaptive synchronization problem for a kind of stochastic Markovian jump neural networks with mode-dependent and unbounded distributed delays. By virtue of the Lyapunov stability theory and the stochastic analysis technique, a generalized LaSalle-type invariance principle for stochastic Markovian differential delay equations is utilized to investigate the globally almost surely asymptotical stability of the error dynamical system in the mean-square sense.Chapter 3, the globally stochastic synchronization problem for a class of neutral-type chaotic neural networks with Markovian jumping parameters under impulsive perturbations. By virtue of drive response concept and time-delay feedback control techniques, by using the Lyapunov functional method,Jensen integral inequality, a novel reciprocal convex lemma and the free-weight matrix method, a novel sufficient condition is derived to ensure the asymptotic synchronization of two identical Markovian jumping chaotic delayed neural networks with impulsive perturbation. The proposed results, which do not require the differentiability and monotonicity of the activation functions, can be easily checked via Matlab software. Finally, a numerical example with their simulations is provided to illustrate the effectiveness of the presented synchronization scheme...
Keywords/Search Tags:Lyapunov-Krasovskii function, Stochastically synchronization, Markovian jump, Chaotic neural networks
PDF Full Text Request
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