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Synchronization of memristive BAM neural networks with leakage delay and additive time-varying delay components via sampled-data control

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Listed:
  • Wang, Weiping
  • Yu, Minghui
  • Luo, Xiong
  • Liu, Linlin
  • Yuan, Manman
  • Zhao, Wenbing

Abstract

In this paper, the global asymptotic stability of memristive bidirectional associative memory neural networks with leakage delay and two additive time-varying delays is firstly studied. Then, we propose a novel sampled-data feedback controller to guarantee the synchronization of system based on drive/response concept. In particular, taking full advantage of the input delay approach, the Lyapunov function method and the Jensen’s inequality theory, several sufficient conditions are obtained. Finally, two numerical simulation examples show the effectiveness of the designed sampled-data control strategy. Furthermore, our results can be applied to simulate the associative memory function of brain-like robots, large-scale information storage, etc.

Suggested Citation

  • Wang, Weiping & Yu, Minghui & Luo, Xiong & Liu, Linlin & Yuan, Manman & Zhao, Wenbing, 2017. "Synchronization of memristive BAM neural networks with leakage delay and additive time-varying delay components via sampled-data control," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 84-97.
    • Handle: RePEc:eee:chsofr:v:104:y:2017:i:c:p:84-97
    DOI: 10.1016/j.chaos.2017.08.011
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    References listed on IDEAS

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    1. R. Samidurai & S. Rajavel & Jinde Cao & Ahmad Alsaedi & Fuad Alsaadi & Bashir Ahmad, 2017. "Delay-partitioning approach to stability analysis of state estimation for neutral-type neural networks with both time-varying delays and leakage term via sampled-data control," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(8), pages 1752-1765, June.
    2. Mathiyalagan, K. & Park, Ju H. & Sakthivel, R., 2015. "Synchronization for delayed memristive BAM neural networks using impulsive control with random nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 967-979.
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    1. Yuan, Manman & Wang, Weiping & Luo, Xiong & Liu, Linlin & Zhao, Wenbing, 2018. "Finite-time anti-synchronization of memristive stochastic BAM neural networks with probabilistic time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 244-260.
    2. Syed Ali, M. & Narayanan, Govindasamy & Shekher, Vineet & Alsulami, Hamed & Saeed, Tareq, 2020. "Dynamic stability analysis of stochastic fractional-order memristor fuzzy BAM neural networks with delay and leakage terms," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    3. Yuhao Lu & Nicholas C Coops, 2018. "Bright lights, big city: Causal effects of population and GDP on urban brightness," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-15, July.
    4. Chen, Chuan & Li, Lixiang & Peng, Haipeng & Kurths, Jürgen & Yang, Yixian, 2018. "Fixed-time synchronization of hybrid coupled networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 49-56.
    5. Li, Tao & Tang, Xiaoling & Qian, Wei & Fei, Shumin, 2019. "Hybrid-delay-dependent approach to synchronization in distributed delay neutral neural networks," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 449-463.
    6. Wang, Weiping & Jia, Xiao & Luo, Xiong & Kurths, Jürgen & Yuan, Manman, 2019. "Fixed-time synchronization control of memristive MAM neural networks with mixed delays and application in chaotic secure communication," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 85-96.
    7. Ávalos-Ruiz, L.F. & Zúñiga-Aguilar, C.J. & Gómez-Aguilar, J.F. & Escobar-Jiménez, R.F. & Romero-Ugalde, H.M., 2018. "FPGA implementation and control of chaotic systems involving the variable-order fractional operator with Mittag–Leffler law," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 177-189.
    8. Bin Zhang & Jiaxi Ye & Xing Bi & Chao Feng & Chaojing Tang, 2018. "Ffuzz: Towards full system high coverage fuzz testing on binary executables," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-16, May.
    9. Chen, Dazhao & Zhang, Zhengqiu, 2022. "Finite-time synchronization for delayed BAM neural networks by the approach of the same structural functions," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    10. Zhen Yang & Zhengqiu Zhang, 2022. "Finite-Time Synchronization Analysis for BAM Neural Networks with Time-Varying Delays by Applying the Maximum-Value Approach with New Inequalities," Mathematics, MDPI, vol. 10(5), pages 1-16, March.

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