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Fixed-time projective synchronization of memristive neural networks with discrete delay

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Listed:
  • Chen, Chuan
  • Li, Lixiang
  • Peng, Haipeng
  • Yang, Yixian
  • Mi, Ling
  • Qiu, Baolin

Abstract

In this paper, the fixed-time projective synchronization of memristive neural networks (MNNs) with discrete delay is studied for the first time. In the circuit implementation of memristive neural network, the synapses are modeled by memristors. Compared with common neural networks, memristive neural network can simulate the human brain better. The fixed-time controller designed in this paper is simplest among all the controllers that are used to study fixed-time stability/synchronization. Since fixed-time stability, fixed-time synchronization and fixed-time anti-synchronization are all special cases of fixed-time projective synchronization, some existing results about the stability/synchronization of MNNs can be regarded as the corollaries of our theoretical results. Numerical simulations are provided to verify the theoretical results.

Suggested Citation

  • Chen, Chuan & Li, Lixiang & Peng, Haipeng & Yang, Yixian & Mi, Ling & Qiu, Baolin, 2019. "Fixed-time projective synchronization of memristive neural networks with discrete delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
  • Handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119313019
    DOI: 10.1016/j.physa.2019.122248
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    References listed on IDEAS

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    Cited by:

    1. Feng, Liang & Hu, Cheng & Yu, Juan & Jiang, Haijun & Wen, Shiping, 2021. "Fixed-time Synchronization of Coupled Memristive Complex-valued Neural Networks," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    2. Xu, Yao & Li, Wenxue, 2020. "Finite-time synchronization of fractional-order complex-valued coupled systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    3. He, Jin-Man & Pei, Li-Jun, 2023. "Function matrix projection synchronization for the multi-time delayed fractional order memristor-based neural networks with parameter uncertainty," Applied Mathematics and Computation, Elsevier, vol. 454(C).
    4. Xiang, Jianglian & Ren, Junwu & Tan, Manchun, 2022. "Stability analysis for memristor-based stochastic multi-layer neural networks with coupling disturbance," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    5. Li, Wenhua & Gao, Xingbao & Li, Ruoxia, 2020. "Stability and synchronization control of inertial neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 367(C).
    6. Yang, Jinrong & Chen, Guici & Wen, Shiping & Wang, Leimin, 2023. "Finite-time dissipative control for discrete-time memristive neural networks via interval matrix method," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    7. Xiao, Lin & Li, Linju & Cao, Penglin & He, Yongjun, 2023. "A fixed-time robust controller based on zeroing neural network for generalized projective synchronization of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    8. Kumar, Ankit & Das, Subir & Singh, Sunny & Rajeev,, 2023. "Quasi-projective synchronization of inertial complex-valued recurrent neural networks with mixed time-varying delay and mismatched parameters," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    9. Pu, Hao & Li, Fengjun, 2023. "Fixed/predefined-time synchronization of complex-valued discontinuous delayed neural networks via non-chattering and saturation control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    10. Zhao, Mingfang & Li, Hong-Li & Zhang, Long & Hu, Cheng & Jiang, Haijun, 2023. "Quasi-synchronization of discrete-time fractional-order quaternion-valued memristive neural networks with time delays and uncertain parameters," Applied Mathematics and Computation, Elsevier, vol. 453(C).
    11. Pan, Jinsong & Zhang, Zhengqiu, 2021. "Finite-time synchronization for delayed complex-valued neural networks via the exponential-type controllers of time variable," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    12. Fu, Qianhua & Zhong, Shouming & Shi, Kaibo, 2021. "Exponential synchronization of memristive neural networks with inertial and nonlinear coupling terms: Pinning impulsive control approaches," Applied Mathematics and Computation, Elsevier, vol. 402(C).

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