Volume 43 Issue 8
Aug.  2022
Turn off MathJax
Article Contents
LIU Feiyang, LI Bing. Event-Based State Estimation of Complex-Valued Neural Networks With Mixed Delays[J]. Applied Mathematics and Mechanics, 2022, 43(8): 911-919. doi: 10.21656/1000-0887.420359
Citation: LIU Feiyang, LI Bing. Event-Based State Estimation of Complex-Valued Neural Networks With Mixed Delays[J]. Applied Mathematics and Mechanics, 2022, 43(8): 911-919. doi: 10.21656/1000-0887.420359

Event-Based State Estimation of Complex-Valued Neural Networks With Mixed Delays

doi: 10.21656/1000-0887.420359
  • Received Date: 2021-11-25
  • Rev Recd Date: 2022-01-06
  • Available Online: 2022-07-06
  • Publish Date: 2022-08-01
  • The event-based state estimation problem was investigated for a class of complex-valued neural networks with mixed delays. Based on the measurement output, a novel event-triggering scheme was introduced to reduce the frequency of updating while ensuring the estimation performance. A waiting time was first employed to avoid the Zeno phenomenon. By means of the Lyapunov direct method and some properties of complex-valued matrices, a sufficient criterion was established to guarantee the globally asymptotic stability for the error system. The weighted parameters and gain matrices were designed with resort to the feasible solution of matrix inequalities. A numerical simulation example illustrates the effectiveness of the proposed method.

  • loading
  • [1]
    TAN K, GOU H. Complex-valued neural networks: advances and applications[book review[J]. IEEE Computational Intelligence Magazine, 2013, 8(2): 77-79. doi: 10.1109/MCI.2013.2247895
    [2]
    HUANG H, HUANG T, CHEN X, et al. Exponential stabilization of delayed recurrent neural networks: a state estimation based approach[J]. Neural Networks, 2013, 48: 153-157. doi: 10.1016/j.neunet.2013.08.006
    [3]
    LEE T, PARK J. Stability analysis of sampled-data systems via free-matrix-based time-dependent discontinuous lyapunov approach[J]. IEEE Transactions on Automatic Control, 2017, 62(7): 3653-3657. doi: 10.1109/TAC.2017.2670786
    [4]
    SHAO H, LI H, ZHU C. New stability results for delayed neural networks[J]. Applied Mathematics and Computation, 2017, 311: 324-334.
    [5]
    XU N, SUN L. Synchronization control of markov jump neural networks with mixed time-varying delay and parameter uncertain based on sample point controller[J]. Nonlinear Dynamics, 2019, 98(3): 1877-1890. doi: 10.1007/s11071-019-05293-y
    [6]
    SONG Q, SHU H, ZHAO Z, et al. Lagrange stability analysis for complex-valued neural networks with leakage delay and mixed time-varying delays[J]. Neurocomputing, 2017, 244(28): 33-41.
    [7]
    JIAN J, WAN P. Global exponential convergence of fuzzy complex-valued neural networks with time-varying delays and impulsive effects[J]. Fuzzy Sets and Systems, 2018, 338: 23-39. doi: 10.1016/j.fss.2017.12.001
    [8]
    张磊, 宋乾坤. 带有比例时滞的复值神经网络全局指数稳定性[J]. 应用数学和力学, 2018, 39(5): 584-591

    ZHANG Lei, SONG Qiankun. Global exponential stability of complex-valued neural networks with proportional delays[J]. Applied Mathematics and Mechanics, 2018, 39(5): 584-591.(in Chinese)
    [9]
    TIAN G, GU Y, SHI D, et al. Neural-network-based power system state estimation with extended observability[J]. Journal of Modern Power Systems and Clean Energy, 2021, 9(5): 1043-1053. doi: 10.35833/MPCE.2020.000362
    [10]
    YIN X, LIU J. Event-triggered state estimation of linear systems using moving horizon estimation[J]. IEEE Transactions on Control Systems Technology, 2021, 29(2): 901-909. doi: 10.1109/TCST.2020.2978908
    [11]
    杜雨薇, 李兵, 宋乾坤. 事件触发下混合时滞神经网络的状态估计[J]. 应用数学和力学, 2020, 41(8): 887-898

    DU Yuwei, LI Bing, SONG Qiankun. Event-based state estimation for neural network with time-varying delay and infinite-distributed delay[J]. Applied Mathematics and Mechanics, 2020, 41(8): 887-898.(in Chinese)
    [12]
    AHN C K. Switched exponential state estimation of neural networks based on passivity theory[J]. Nonlinear Dynamics, 2012, 67(1): 573-586. doi: 10.1007/s11071-011-0010-x
    [13]
    PARK J H, MATHIYALAGAN K, SAKTHIVEI R. Fault estimation for discrete-time switched nonlinear systems with discrete and distributed delays[J]. International Journal of Robust and Nonlinear Control, 2016, 26(17): 3755-3771. doi: 10.1002/rnc.3532
    [14]
    XU Y, LU R, PENG H, et al. Asynchronous dissipative state estimation for stochastic complex networks with quantized jumping coupling and uncertain measurements[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(2): 268-277. doi: 10.1109/TNNLS.2015.2503772
    [15]
    HU J, LI N, LIU X, et al. Sampled-data state estimation for delayed neural networks with Markovian jumping parameters[J]. Nonlinear Dynamics, 2013, 73(1/2): 275-284.
    [16]
    GONG W, LIANG J, KAN X, et al. Robust state estimation for delayed complex-valued neural networks[J]. Neural Processing Letters, 2017, 46(3): 1009-1029. doi: 10.1007/s11063-017-9626-2
    [17]
    GONG W, LIANG J, KAN X, et al. Robust state estimation for stochastic complex-valued neural networks with sampled-data[J]. Neural Computing and Applications, 2019, 31: 523-542.
    [18]
    WAKAIKI M, SANO H. Event-triggered control of infinite-dimensional systems[J]. SIAM Journal on Control and Optimization, 2020, 58(2): 605-635. doi: 10.1137/18M1179717
    [19]
    CHENG B, WU Z, LI Z. Distributed edge-based event-triggered formation control[J]. IEEE Transactions on Cybernetics, 2020, 51(3): 1241-1252.
    [20]
    CHENG Y, UGRINOVSKII V. Event-triggered leader-follower tracking control for interconnected systems[J]. International Journal of Robust and Nonlinear Control, 2020, 30(18): 7883-7908. doi: 10.1002/rnc.5154
    [21]
    WANG X, WANG Z, SONG Q, et al. A waiting-time-based event-triggered scheme for stabilization of complex-valued neural networks[J]. Neural Networks, 2020, 121: 329-338. doi: 10.1016/j.neunet.2019.09.032
    [22]
    TAN Y, DU D, QI Q. State estimation for Markovian jump systems with an event-triggered communication scheme[J]. Circuits Systems and Signal Processing, 2017, 36(1): 2-24. doi: 10.1007/s00034-016-0288-5
    [23]
    WANG J, ZHANG X, HAN Q. Event-triggered generalized dissipativity filtering for neural networks with time-varying delays[J]. IEEE Transactions on Neural Networks and Learning Systens, 2016, 27(1): 77-88. doi: 10.1109/TNNLS.2015.2411734
    [24]
    GUNASEKARAN N, ZHAI G. Sampled-data state-estimation of delayed complex-valued neural networks[J]. International Journal of Systems Science, 2019, 51(2): 303-312.
    [25]
    WANG Z, LIU Y, LIU X. State estimation for jumping recurrent neural networks with discrete and distributed delays[J]. Neural Networks, 2009, 22(1): 41-48. doi: 10.1016/j.neunet.2008.09.015
    [26]
    YAN S, YANG F, GU, Z. Derivative-based event-triggered control for networked systems with quantization[J]. Applied Mathematics and Computation, 2020, 383: 125359. doi: 10.1016/j.amc.2020.125359
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(4)

    Article Metrics

    Article views (510) PDF downloads(43) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return