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H∞ performance state estimation of delayed static neural networks based on an improved proportional-integral estimator

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  • Tan, Guoqiang
  • Wang, Zhanshan
  • Li, Cong

Abstract

In this paper, an improved proportional-integral (PI) estimator is presented to analyze the problem of H∞ performance state estimation of static neural networks with disturbance. An exponential gain term is added to the PI estimator, which leads to the convenience of analysis and design. In order to guarantee the H∞ performance state estimation, a less conservative delay-dependent criterion is derived by using an improved reciprocally convex inequality. Finally, simulation results are given to verify the advantage of the presented approach.

Suggested Citation

  • Tan, Guoqiang & Wang, Zhanshan & Li, Cong, 2020. "H∞ performance state estimation of delayed static neural networks based on an improved proportional-integral estimator," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    • Handle: RePEc:eee:apmaco:v:370:y:2020:i:c:s0096300319309002
    DOI: 10.1016/j.amc.2019.124908
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    References listed on IDEAS

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    Cited by:

    1. Tian, Yufeng & Wang, Zhanshan, 2021. "A new result on H∞ performance state estimation for static neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    2. Tian, Yufeng & Wang, Zhanshan, 2021. "Dissipative filtering for singular Markovian jump systems with generally hybrid transition rates," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    3. Sakthivel, Ramalingam & Sakthivel, Rathinasamy & Kwon, Oh-Min & Selvaraj, Palanisamy, 2021. "Disturbance rejection for singular semi-Markov jump neural networks with input saturation," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    4. Wang, Xinwei & Liu, Jie & Peng, Haijun & Zhao, Xudong, 2022. "An iterative framework to solve nonlinear optimal control with proportional delay using successive convexification and symplectic multi-interval pseudospectral scheme," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    5. Zhang, Juan & Zhang, Huaguang & Li, Weihua & Li, Keqin, 2021. "Distributed edge-event triggered consensus control for multi-agent systems by edge-based asynchronous communications," Applied Mathematics and Computation, Elsevier, vol. 397(C).
    6. Yu Yao & Guodong Zhang & Yan Li, 2023. "Fixed/Preassigned-Time Stabilization for Complex-Valued Inertial Neural Networks with Distributed Delays: A Non-Separation Approach," Mathematics, MDPI, vol. 11(10), pages 1-17, May.

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