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Synchronization control of stochastic delayed neural networks

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  • Yu, Wenwu
  • Cao, Jinde

Abstract

In this paper, synchronization control of stochastic neural networks with time-varying delays has been considered. A novel control method is given using the Lyapunov functional method and linear matrix inequality (LMI) approach. Several sufficient conditions have been derived to ensure the global asymptotical stability in mean square for the error system, and thus the drive system synchronize with the response system. Also, the estimation gains can be obtained. With these new and effective methods, synchronization can be achieved. Simulation results are given to verify the theoretical analysis in this paper.

Suggested Citation

  • Yu, Wenwu & Cao, Jinde, 2007. "Synchronization control of stochastic delayed neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 252-260.
    • Handle: RePEc:eee:phsmap:v:373:y:2007:i:c:p:252-260
    DOI: 10.1016/j.physa.2006.04.105
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    References listed on IDEAS

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    1. Küchler, Uwe & Platen, Eckhard, 2000. "Strong discrete time approximation of stochastic differential equations with time delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 54(1), pages 189-205.
    2. Küchler, Uwe & Platen, Eckhard, 2002. "Weak discrete time approximation of stochastic differential equations with time delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(6), pages 497-507.
    3. Wang, Weiwei & Cao, Jinde, 2006. "Synchronization in an array of linearly coupled networks with time-varying delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 197-211.
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    5. Li, Chunguang & Li, Shaowen & Liao, Xiaofeng & Yu, Juebang, 2004. "Synchronization in coupled map lattices with small-world delayed interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(3), pages 365-370.
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    Citations

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    Cited by:

    1. Feng, Xiaomei & Zhang, Fengqin & Wang, Wenjuan, 2011. "Global exponential synchronization of delayed fuzzy cellular neural networks with impulsive effects," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 9-16.
    2. Wang, Liming & Wu, Kai-Ning & Zhu, Ya-Nan & Ding, Xiaohua, 2016. "Mean square H∞ synchronization of coupled stochastic partial differential systems," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 386-393.
    3. Li, Tao & Fei, Shu-min & Zhang, Kan-jian, 2008. "Synchronization control of recurrent neural networks with distributed delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 982-996.
    4. Park, Ju H., 2009. "Synchronization of cellular neural networks of neutral type via dynamic feedback controller," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1299-1304.
    5. Zhang, Hongmei & Cao, Jinde & Xiong, Lianglin, 2019. "Novel synchronization conditions for time-varying delayed Lur’e system with parametric uncertainty," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 224-236.
    6. Karimi, Hamid Reza & Maass, Peter, 2009. "Delay-range-dependent exponential H∞ synchronization of a class of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1125-1135.
    7. Wang, Kai & Teng, Zhidong & Jiang, Haijun, 2008. "Adaptive synchronization of neural networks with time-varying delay and distributed delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 631-642.
    8. Subramanian, K. & Muthukumar, P. & Lakshmanan, S., 2018. "State feedback synchronization control of impulsive neural networks with mixed delays and linear fractional uncertainties," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 267-281.
    9. Yu, Wenwu & Cao, Jinde, 2007. "Adaptive synchronization and lag synchronization of uncertain dynamical system with time delay based on parameter identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 467-482.

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