Global Stability and Synchronization of Markovian Switching Neural Networks with Stochastic Perturbation and Impulsive Delay

2015 ◽  
Vol 34 (8) ◽  
pp. 2457-2474 ◽  
Author(s):  
Wei Zhang ◽  
Chuandong Li ◽  
Tingwen Huang ◽  
Jiangtao Qi
Keyword(s):  
Neural Networks ◽  
Global Stability ◽  
Stochastic Perturbation ◽  
Markovian Switching ◽  
Impulsive Delay

Adaptive almost sure asymptotically stability for neutral-type neural networks with stochastic perturbation and Markovian switching

2015 ◽  
Vol 156 ◽  
pp. 151-156 ◽  
Author(s):  
Liuwei Zhou ◽  
Zhijie Wang ◽  
Xiantao Hu ◽  
Bo Chu ◽  
Wuneng Zhou
Keyword(s):  
Neural Networks ◽  
Neutral Type ◽  
Stochastic Perturbation ◽  
Markovian Switching

scholarly journals Almost Sure Asymptotical Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Wuneng Zhou ◽  
Xueqing Yang ◽  
Jun Yang ◽  
Anding Dai ◽  
Huashan Liu
Keyword(s):  
Neural Networks ◽  
Neutral Type ◽  
Stochastic Perturbation ◽  
Adaptive Controller ◽  
Functional Method ◽  
Markovian Switching ◽  
Adaptive Synchronization ◽  
Linear Matrix ◽  
Lyapunov Functional Method ◽  
New Criterion

The problem of almost sure (a.s.) asymptotic adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching is researched. Firstly, we proposed a new criterion of a.s. asymptotic stability for a general neutral-type stochastic differential equation which extends the existing results. Secondly, based upon this stability criterion, by making use of Lyapunov functional method and designing an adaptive controller, we obtained a condition of a.s. asymptotic adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching. The synchronization condition is expressed as linear matrix inequality which can be easily solved by Matlab. Finally, we introduced a numerical example to illustrate the effectiveness of the method and result obtained in this paper.

Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching Parameters

2014 ◽  
Vol 44 (12) ◽  
pp. 2848-2860 ◽  
Author(s):  
Wuneng Zhou ◽  
Qingyu Zhu ◽  
Peng Shi ◽  
Hongye Su ◽  
Jian'an Fang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Neutral Type ◽  
Stochastic Perturbation ◽  
Markovian Switching ◽  
Adaptive Synchronization

scholarly journals Existence and global stability of periodic solution for delayed discrete high-order Hopfield-type neural networks

2005 ◽  
Vol 2005 (3) ◽  
pp. 281-297 ◽  
Author(s):  
Hong Xiang ◽  
Ke-Ming Yan ◽  
Bai-Yan Wang
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Global Stability ◽  
A Priori Estimates ◽  
A Priori ◽  
Sufficient Conditions ◽  
Coincidence Degree ◽  
Degree Theory ◽  
High Order ◽  
Priori Estimates

By using coincidence degree theory as well as a priori estimates and Lyapunov functional, we study the existence and global stability of periodic solution for discrete delayed high-order Hopfield-type neural networks. We obtain some easily verifiable sufficient conditions to ensure that there exists a unique periodic solution, and all theirs solutions converge to such a periodic solution.

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