Robust Stabilization of Memristor-based Coupled Neural Networks with Time-varying Delays

被引：20
作者：
Fu, Qianhua [1 ,2 ]
Cai, Jingye [2 ]
Zhong, Shouming [3 ]
机构：
[1] Xihua Univ, Sch Elect Engn & Elect Informat, Chengdu 610039, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Informat & Software Engn, Chengdu 610054, Sichuan, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2019年 / 17卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Coupled neural networks; memristor; robust stabilization; T-S fuzzy; time-varying delays; EXPONENTIAL SYNCHRONIZATION; STABILITY; SYSTEMS;
D O I：
10.1007/s12555-018-0936-6
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The robust stabilization problem of memristor-based coupled neural networks (MNNs) is addressed in this paper. Firstly, the fuzzy model of MNNs is obtained by considering the properties of memristor and corresponding circuit, some predictable assumptions on the boundedness and Lipschitz continuity of activation functions are formulated. Secondly, based on T-S fuzzy theory and Lyapunov-Krasovskii functional method, robust stabilization criteria are derived in form of linear matrix inequalities (LMIs). Finally a numerical example is presented to demonstrate the effectiveness of the proposed robust stabilization criteria, which well supports theoretical results.
引用
收藏
页码：2666 / 2676
页数：11
相关论文
共 28 条
[1]   State estimation of fractional-order delayed memristive neural networks [J].
Bao, Haibo ;
Cao, Jinde ;
Kurths, Juergen .
NONLINEAR DYNAMICS, 2018, 94 (02) :1215-1225
[2]   H∞ state estimation of stochastic memristor-based neural networks with time-varying delays [J].
Bao, Haibo ;
Cao, Jinde ;
Kurths, Juergen ;
Alsaedi, Ahmed ;
Ahmad, Bashir .
NEURAL NETWORKS, 2018, 99 :79-91
[3]   Adaptive synchronization of fractional-order memristor-based neural networks with time delay [J].
Bao, Haibo ;
Park, Ju H. ;
Cao, Jinde .
NONLINEAR DYNAMICS, 2015, 82 (03) :1343-1354
[4]   Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay [J].
Bao, Haibo ;
Park, Ju H. ;
Cao, Jinde .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (01) :190-201
[5]   Robust stability analysis of quaternion-valued neural networks via LMI approach [J].
Chen, Xiaofeng ;
Li, Lianjie ;
Li, Zhongshan .
ADVANCES IN DIFFERENCE EQUATIONS, 2018,
[6]   MEMRISTOR - MISSING CIRCUIT ELEMENT [J].
CHUA, LO .
IEEE TRANSACTIONS ON CIRCUIT THEORY, 1971, CT18 (05) :507-+
[7]   Input-to-state stability of discrete-time memristive neural networks with two delay components [J].
Fu, Qianhua ;
Cai, Jingye ;
Zhong, Shouming ;
Yu, Yongbin ;
Shan, Yaonan .
NEUROCOMPUTING, 2019, 329 :1-11
[8]   Synaptic long-term potentiation realized in Pavlov's dog model based on a NiOx-based memristor [J].
Hu, S. G. ;
Liu, Y. ;
Liu, Z. ;
Chen, T. P. ;
Yu, Q. ;
Deng, L. J. ;
Yin, Y. ;
Hosaka, Sumio .
JOURNAL OF APPLIED PHYSICS, 2014, 116 (21)
[9]   Ferroelectric Tunnel Memristor [J].
Kim, D. J. ;
Lu, H. ;
Ryu, S. ;
Bark, C-W. ;
Eom, C-B. ;
Tsymbal, E. Y. ;
Gruverman, A. .
NANO LETTERS, 2012, 12 (11) :5697-5702
[10]   Neural Synaptic Weighting With a Pulse-Based Memristor Circuit [J].
Kim, Hyongsuk ;
Sah, Maheshwar Pd. ;
Yang, Changju ;
Roska, Tamas ;
Chua, Leon O. .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2012, 59 (01) :148-158
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