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Robust passivity analysis for uncertain neural networks with leakage delay and additive time-varying delays by using general activation function

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  • Cao, Yang
  • Samidurai, R.
  • Sriraman, R.

Abstract

This article deals with the robust passivity analysis problem for uncertain neural networks with both leakage delay and additive time-varying delays by using a more general activation function technique. The information of activation function which is ignored in the existing results is taken into account in this paper. Based on Lyapunov stability theory, a proper Lyapunov–Krasovskii functional (LKF) with some new terms is constructed. The less conservative delay-dependent stability criteria have been obtained by applying a newly developed integral inequality that includes Jensen’s inequality and a Wirtinger-based integral inequality as a special case. Some sufficient conditions are achieved to guarantee the stability and passivity of the addressed system model. All the proposed results are formulated as linear matrix inequalities (LMIs). Finally, three numerical cases are simulated to show the effectiveness and benefits of our proposed method.

Suggested Citation

  • Cao, Yang & Samidurai, R. & Sriraman, R., 2019. "Robust passivity analysis for uncertain neural networks with leakage delay and additive time-varying delays by using general activation function," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 57-77.
    • Handle: RePEc:eee:matcom:v:155:y:2019:i:c:p:57-77
    DOI: 10.1016/j.matcom.2017.10.016
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    References listed on IDEAS

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    1. Samidurai, Rajendran & Manivannan, Raman, 2015. "Robust passivity analysis for stochastic impulsive neural networks with leakage and additive time-varying delay components," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 743-762.
    2. Rajavel, S. & Samidurai, R. & Cao, Jinde & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Finite-time non-fragile passivity control for neural networks with time-varying delay," Applied Mathematics and Computation, Elsevier, vol. 297(C), pages 145-158.
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    Cited by:

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    3. Zhang, Shuai & Yang, Yongqing & Sui, Xin & Xu, Xianyu, 2019. "Finite-time synchronization of memristive neural networks with parameter uncertainties via aperiodically intermittent adjustment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
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    5. Song, Xingxing & Lu, Hongqian & Xu, Yao & Zhou, Wuneng, 2022. "H∞ synchronization of semi-Markovian jump neural networks with random sensor nonlinearities via adaptive event-triggered output feedback control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 198(C), pages 1-19.
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    8. Wang, Shuzhan & Zhang, Ziye & Lin, Chong & Chen, Jian, 2021. "Fixed-time synchronization for complex-valued BAM neural networks with time-varying delays via pinning control and adaptive pinning control," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    9. Owolabi, Kolade M. & Gómez-Aguilar, J.F. & Karaagac, Berat, 2019. "Modelling, analysis and simulations of some chaotic systems using derivative with Mittag–Leffler kernel," Chaos, Solitons & Fractals, Elsevier, vol. 125(C), pages 54-63.
    10. Li, Liangchen & Xu, Rui & Lin, Jiazhe, 2020. "Lagrange stability for uncertain memristive neural networks with Lévy noise and leakage delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    11. Harshavarthini, S. & Sakthivel, R. & Ma, Yong-Ki & Muslim, M., 2020. "Finite-time resilient fault-tolerant investment policy scheme for chaotic nonlinear finance system," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    12. Wang, Yao & Guo, Jun & Liu, Guobao & Lu, Junwei & Li, Fangyuan, 2021. "Finite-time sampled-data synchronization for uncertain neutral-type semi-Markovian jump neural networks with mixed time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    13. Wang, Limin & Song, Qiankun, 2020. "Pricing policies for dual-channel supply chain with green investment and sales effort under uncertain demand," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 79-93.
    14. Gao, Panqing & Ye, Renyu & Zhang, Hai & Stamova, Ivanka & Cao, Jinde, 2024. "Asymptotic stability and quantitative synchronization of fractional competitive neural networks with multiple restrictions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 338-353.

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