Graph-Theoretic Approach to Finite-Time Synchronization for Fuzzy Cohen–Grossberg Neural Networks with Mixed Delays and Discontinuous Activations

This paper investigates finite-time synchronization for fuzzy Cohen–Grossberg neural networks (FCGNNs) with mixed delays and discontinuous activations via state-feedback control. The features of FCGNNs, discrete time delays, distributed delays and discontinuous activations are taken into account whi...

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Published inNeural processing letters Vol. 52; no. 1; pp. 905 - 933
Main Authors Xu, Dongsheng, Xu, Chengqiang, Liu, Ming
Format Journal Article
LanguageEnglish
Published New York Springer US 01.08.2020
Springer Nature B.V
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Abstract This paper investigates finite-time synchronization for fuzzy Cohen–Grossberg neural networks (FCGNNs) with mixed delays and discontinuous activations via state-feedback control. The features of FCGNNs, discrete time delays, distributed delays and discontinuous activations are taken into account which makes our networks more general and practical in comparison with the most existing Cohen–Grossberg neural networks. Two switching state-feedback controllers designed for the implement of finite-time synchronization can be used to effectively overcome the limitations of the traditional continuous linear feedback controllers. Different from previous work, graph theory and Lyapunov method are used to study finite-time synchronization of FCGNNs for the first time in this paper, then some sufficient criteria are obtained to guarantee the finite-time synchronization of FCGNNs. In particular, it is worth noting that the settling time for finite-time synchronization is closely related to the topological structure of FCNNs. Finally, two numerical examples are given to verify the feasibility and effectiveness of the theoretical results.
AbstractList This paper investigates finite-time synchronization for fuzzy Cohen–Grossberg neural networks (FCGNNs) with mixed delays and discontinuous activations via state-feedback control. The features of FCGNNs, discrete time delays, distributed delays and discontinuous activations are taken into account which makes our networks more general and practical in comparison with the most existing Cohen–Grossberg neural networks. Two switching state-feedback controllers designed for the implement of finite-time synchronization can be used to effectively overcome the limitations of the traditional continuous linear feedback controllers. Different from previous work, graph theory and Lyapunov method are used to study finite-time synchronization of FCGNNs for the first time in this paper, then some sufficient criteria are obtained to guarantee the finite-time synchronization of FCGNNs. In particular, it is worth noting that the settling time for finite-time synchronization is closely related to the topological structure of FCNNs. Finally, two numerical examples are given to verify the feasibility and effectiveness of the theoretical results.
Author Xu, Dongsheng
Xu, Chengqiang
Liu, Ming
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  givenname: Chengqiang
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  fullname: Xu, Chengqiang
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  givenname: Ming
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  surname: Liu
  fullname: Liu, Ming
  email: liuming_girl@163.com
  organization: Department of Mathematics, Northeast Forestry University
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crossref_primary_10_1109_TFUZZ_2021_3059953
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Keywords Finite-time synchronization
Switching state-feedback control
Distributed delays
Fuzzy Cohen–Grossberg neural networks
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Snippet This paper investigates finite-time synchronization for fuzzy Cohen–Grossberg neural networks (FCGNNs) with mixed delays and discontinuous activations via...
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SubjectTerms Artificial Intelligence
Artificial neural networks
Complex Systems
Computational Intelligence
Computer Science
Control systems
Euclidean space
Feedback control
Fuzzy logic
Graph theory
Money markets
Neural networks
State feedback
Time synchronization
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  providerName: Springer Nature
Title Graph-Theoretic Approach to Finite-Time Synchronization for Fuzzy Cohen–Grossberg Neural Networks with Mixed Delays and Discontinuous Activations
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