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Asymptotically stable high-order neutral cellular neural networks with proportional delays and D operators

Author

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  • Huang, Chuangxia
  • Su, Renli
  • Cao, Jinde
  • Xiao, Songlin

Abstract

This paper aims to deal with the asymptotic stability of high-order neutral cellular neural networks (HNCNNs) incorporating proportional delays and D operators. Employing Lyapunov method, inequality technique and concise mathematical analysis proof, sufficient criteria on the global exponential asymptotical stability of the proposed HNCNNs are obtained. The main results provide us some light for designing stable HNCNNs and complement some earlier publications. In addition, simulations show that the theoretical convergence is in excellent agreement with the numerically observed behavior.

Suggested Citation

  • Huang, Chuangxia & Su, Renli & Cao, Jinde & Xiao, Songlin, 2020. "Asymptotically stable high-order neutral cellular neural networks with proportional delays and D operators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 127-135.
    • Handle: RePEc:eee:matcom:v:171:y:2020:i:c:p:127-135
    DOI: 10.1016/j.matcom.2019.06.001
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    References listed on IDEAS

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    1. Yu, Yuehua, 2016. "Global exponential convergence for a class of HCNNs with neutral time-proportional delays," Applied Mathematics and Computation, Elsevier, vol. 285(C), pages 1-7.
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    Cited by:

    1. Huang, Chuangxia & Liu, Bingwen & Qian, Chaofan & Cao, Jinde, 2021. "Stability on positive pseudo almost periodic solutions of HPDCNNs incorporating D operator," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1150-1163.
    2. Karnan, A. & Nagamani, G., 2022. "Non-fragile state estimation for memristive cellular neural networks with proportional delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 217-231.
    3. Deng, Yunke & Huang, Chuangxia & Cao, Jinde, 2021. "New results on dynamics of neutral type HCNNs with proportional delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 187(C), pages 51-59.
    4. Chen, Yonghui & Zhang, Xian & Xue, Yu, 2022. "Global exponential synchronization of high-order quaternion Hopfield neural networks with unbounded distributed delays and time-varying discrete delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 173-189.
    5. Wang, Junlan & Wang, Xin & Wang, Yantao & Zhang, Xian, 2021. "Non-reduced order method to global h-stability criteria for proportional delay high-order inertial neural networks," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    6. Chao Wang & Yinfang Song & Fengjiao Zhang & Yuxiao Zhao, 2023. "Exponential Stability of a Class of Neutral Inertial Neural Networks with Multi-Proportional Delays and Leakage Delays," Mathematics, MDPI, vol. 11(12), pages 1-14, June.
    7. Chang, Shuang & Wang, Yantao & Zhang, Xian & Wang, Xin, 2023. "A new method to study global exponential stability of inertial neural networks with multiple time-varying transmission delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 211(C), pages 329-340.
    8. Syed Ali, M. & Narayanan, G. & Saroha, Sumit & Priya, Bandana & Thakur, Ganesh Kumar, 2021. "Finite-time stability analysis of fractional-order memristive fuzzy cellular neural networks with time delay and leakage term," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 468-485.
    9. Shen, Shiping & Meng, Xiaofang, 2023. "Finite-time stability of almost periodic solutions of Clifford-valued RNNs with time-varying delays and D operator on time scales," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).

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