Neural Networks2022,Vol.1528.DOI:10.1016/j.neunet.2022.05.009

Set-membership filtering for complex networks with constraint communication channels

Liu, Chang Yang, Lixin Tao, Jie Xu, Yong Huang, Tingwen
Neural Networks2022,Vol.1528.DOI:10.1016/j.neunet.2022.05.009

Set-membership filtering for complex networks with constraint communication channels

Liu, Chang 1Yang, Lixin 1Tao, Jie 1Xu, Yong 1Huang, Tingwen2
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作者信息

  • 1. Sch Automat,Guangdong Univ Technol
  • 2. Dept Sci Program,Texas A&M Univ Qatar
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Abstract

The set-membership filtering is studied for a class of multi-rate sampling complex networks with communication capacity constraint. For reducing communication load, the weighted try-once-discard scheduling protocol is utilized to transmit the most needed measurement. To improve the filtering performance, a novel mixed compensation method is proposed to obtain a compensatory measurement that is closer to the actual value. Accordingly, a mixed compensation dependent filter is designed, and a filtering error system is obtained. Sufficient conditions are established to ensure that the filtering error system satisfies PTk-dependent constraint. Then, a new algorithm is designed to obtain the optimized ellipsoid by minimizing the constraint matrix. Finally, an illustrative example is given to demonstrate the validity of the developed filter. (C) 2022 Elsevier Ltd. All rights reserved.

Key words

Set-membership filtering/Multi-rate sampling complex networks/Weighted try-once-discard protocol/Mixed compensation/FINITE-TIME SYNCHRONIZATION/ARTIFICIAL NEURAL-NETWORKS/INFINITY STATE ESTIMATION/FRACTIONAL-ORDER/SYSTEMS

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出版年

2022
Neural Networks

Neural Networks

EISCI
ISSN:0893-6080
被引量9
参考文献量37
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