Exponential stochastic synchronization of coupled neural networks with adaptive intermittent control
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- 英文论文题名：Exponential stochastic synchronization of coupled neural networks with adaptive intermittent control
- 论文作者：Haiyi Sun ; Ning Li ; Zhongtang Chen ; Shuxian Miao
- 英文论文作者：Haiyi Sun ; Ning Li ; Zhongtang Chen ; Shuxian Miao ; College of Science ; Shenyang Jian Zhu University ; College of Sciences ; Northeastern University
- 年：2017
- 作者机构：College of Science,Shenyang Jian Zhu University;College of Sciences,Northeastern University;
- 英文论文关键词：Coupled neural networks ; Chaotic delayed neural networks ; Exponential stochastic synchronization ; Adaptive periodically intermittent control
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（A）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（A）
- 语种：英文
- 分类号：TP13;TP183
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：238k
- 原文格式：D
- 会议级别：全国
摘要
In this paper, the exponential stochastic synchronization of coupled neural networks via adaptive periodically intermittent control is further investigated. Based on the Lyapunov stability theory combined with the method of the adaptive control,periodically intermittent control and the properties of Weiner process, some simple criteria are derived for the exponential stochastic synchronization of the coupled neural networks with coupling delays under stochastic perturbations. The adaptive periodically intermittent control which we have obtained can cut down control cost. The sufficient conditions of this paper for network synchronization are less conservative and can be applied in a wider area. The numerical example of the stochastically coupled neural networks is given to demonstrate the effectiveness of the control strategies.
In this paper, the exponential stochastic synchronization of coupled neural networks via adaptive periodically intermittent control is further investigated. Based on the Lyapunov stability theory combined with the method of the adaptive control,periodically intermittent control and the properties of Weiner process, some simple criteria are derived for the exponential stochastic synchronization of the coupled neural networks with coupling delays under stochastic perturbations. The adaptive periodically intermittent control which we have obtained can cut down control cost. The sufficient conditions of this paper for network synchronization are less conservative and can be applied in a wider area. The numerical example of the stochastically coupled neural networks is given to demonstrate the effectiveness of the control strategies.
In this paper, the exponential stochastic synchronization of coupled neural networks via adaptive periodically intermittent control is further investigated. Based on the Lyapunov stability theory combined with the method of the adaptive control,periodically intermittent control and the properties of Weiner process, some simple criteria are derived for the exponential stochastic synchronization of the coupled neural networks with coupling delays under stochastic perturbations. The adaptive periodically intermittent control which we have obtained can cut down control cost. The sufficient conditions of this paper for network synchronization are less conservative and can be applied in a wider area. The numerical example of the stochastically coupled neural networks is given to demonstrate the effectiveness of the control strategies.
引文
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[7]H.Alonso,T.Mendonca,and P.Rocha,Hopfield neural networks for on-line parameter estimation,Neural Netw.,22(4):450–462,2009.
[8]J.Cao,P.Li,W.Wang.Global synchronization in arrays of delayed neural networks with constant and delayed coupling.Physics Letters A,353(4):318–325,2006.
[9]H.Sun,Q.Zhang,N.Li.Synchronization control of united complex dynamical networks with multi-links.International Journal Innovative Computing,Information and Control,7(2):927–939,2011.
[10]H.Bao,J.Park and J.Cao,Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay,IEEE Transactions on Neural Networks and Learning Systems,27(1):190–201,2016.
[11]L.Li,D.Ho,J.Cao and J.Lu,Pinning cluster synchronization in an array of coupled neural networks under event-based mechanism,Neural Networks the Official Journal of the International Neural Network Society,76(1):1–12,2015.
[12]X.Yang and J.Cao.Stochastic synchronization of coupled neural networks with intermittent control,Physics Letters A,373(36):3259–3272,2009.
[13]C.Hu,J.Yu,H.Jiang,Z.Teng.Exponential lag synchronization for neural networks with mixed delays via periodically intermittent control.Chaos,20(2):023108,2010.
[14]N.Li,H.Sun,X.Jing,Q.Zhang.Exponential synchronisation of united complex dynamical networks with multi-links via adaptive periodically intermittent control.IET Control Theory Appl.,7(13):1725–1736,2013.
[2]A.Meyer-B¨ase,S.Pilyugin,A.Wismuler,and S.Foo,Local exponential stability of competitive neural networks with different time scales,Eng.Appl.Artificial Intell.,17(3):227–232,2004.
[3]A.Meyer-B¨ase,S.Pilyugin,and Y.Chen,Global exponential stability of competitive neural networks with different time scales,IEEE Trans.Neural Netw.,14(3):716–719,2003.
[4]A.Meyer-B¨ase,F.Ohl,and H.Scheich,Singular perturbation analysis of competitive neural networks with different time scales,Neural Comput.,8(8):1731–1742,1996.
[5]S.Amari,Field theory of self-organizing neural net,IEEE Trans.Syst.Man,Cybern.,B,13(5):741–748,1983.
[6]W.Ding,synchronization of delayed fuzzy cellular neural networks with impulsive effects,Commun.Nonlinear Sci.Numer.Simul.,14(11):3945–3952,2009.
[7]H.Alonso,T.Mendonca,and P.Rocha,Hopfield neural networks for on-line parameter estimation,Neural Netw.,22(4):450–462,2009.
[8]J.Cao,P.Li,W.Wang.Global synchronization in arrays of delayed neural networks with constant and delayed coupling.Physics Letters A,353(4):318–325,2006.
[9]H.Sun,Q.Zhang,N.Li.Synchronization control of united complex dynamical networks with multi-links.International Journal Innovative Computing,Information and Control,7(2):927–939,2011.
[10]H.Bao,J.Park and J.Cao,Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay,IEEE Transactions on Neural Networks and Learning Systems,27(1):190–201,2016.
[11]L.Li,D.Ho,J.Cao and J.Lu,Pinning cluster synchronization in an array of coupled neural networks under event-based mechanism,Neural Networks the Official Journal of the International Neural Network Society,76(1):1–12,2015.
[12]X.Yang and J.Cao.Stochastic synchronization of coupled neural networks with intermittent control,Physics Letters A,373(36):3259–3272,2009.
[13]C.Hu,J.Yu,H.Jiang,Z.Teng.Exponential lag synchronization for neural networks with mixed delays via periodically intermittent control.Chaos,20(2):023108,2010.
[14]N.Li,H.Sun,X.Jing,Q.Zhang.Exponential synchronisation of united complex dynamical networks with multi-links via adaptive periodically intermittent control.IET Control Theory Appl.,7(13):1725–1736,2013.