带有时变时滞和同步切换的忆阻神经网络的全局指数稳定性

Jiang Yinlu; Li Chuandong

doi:10.16383/j.aas.2017.e150066

带有时变时滞和同步切换的忆阻神经网络的全局指数稳定性

doi: 10.16383/j.aas.2017.e150066

蒋音露,
李传东^,

西南大学电子信息工程学院重庆 400715

基金项目:

Natural Science Foundation Project of Chongqing CSTC cstc2014jcyjA40014

the National Natural Science Foundation of China 61374078

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出版历程
- 收稿日期: 2015-06-07
- 录用日期: 2015-10-13
- 刊出日期: 2017-08-20

Globally Exponential Stability of Memristive Neural Networks With Time-varying Delays and Synchronous Switching

Jiang Yinlu,
Li Chuandong^,

College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China

Funds:

Natural Science Foundation Project of Chongqing CSTC cstc2014jcyjA40014

the National Natural Science Foundation of China 61374078

More Information

Author Bio:
Yinlu Jiang received the B.S.degree in communication engineering from Southwest University of Science and Technology, Sichuan, China, in 2013, and presently she is studying for M.S.degree in Signal and Information Processing at Southwest University, Chongqing, China.Her research interests include neural networks, memristive systems, and impulsive dynamical systems.E-mail:jiang yinlu@126.com

Corresponding author: Chuandong Li received the B.S.degree in applied mathematics from Sichuan University, Chengdu, China in 1992, and M.S.degree in operational research and control theory and Ph.D.degree in computer software and theory from Chongqing University, Chongqing, China, in 2001 and 2005, respectively.He has been a Professor at the College of Electronic and Information Engineering, Southwest University, Chongqing, China, since 2012, and has been the IEEE Senior Member since 2010.From November 2006 to November 2008, he served as a Research Fellow in the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China.He has published about more than 100 journal papers.His research interests include computational intelligence, neural networks, memristive systems, chaos control, and synchronization, and impulsive dynamical systems.Corresponding author of this paper.E-mail:licd@cqu.edu.cn

摘要

摘要: 本文建立并研究了一类具有时变时滞和不同切换机制的忆阻神经网络.利用李雅普诺夫稳定性理论，得到了该神经网络平衡点一致稳定性的充分条件，该充分条件直接有效地反映了时变时滞对稳定性的影响.数值模拟结果验证了理论结果的有效性.
- 忆阻神经网络 /
- 同步切换 /
- 时变时滞 /
- 李雅普诺夫函数
Abstract: In this paper, we formulate and investigate a memristive neural networks with time-varying delays and synchronous switching. Conditions are derived which ensure the existence of an equilibrium point and uniform stability for state trajectories of the memristive neural network. The analysis in the paper employs results from the theory of Lyapunov function. Moreover, the proposed stability conditions are straightforward and convenient which can reflect the impact of time-varying delays on the stability. The simulation results demonstrate the effectiveness of the theoretical results.
- Lyapunov function /
- memristive neural networks /
- synchronous switching /
- time-varying delays
Recommended by Associate Editor Zhanshan Wang
注释:

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Fig. 1 Time response curves for memristive neural network with time-varying delays and synchronous switching.

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