Adaptive finite-time cluster synchronization of neutral-type coupled neural networks with mixed delays
This paper investigates the adaptive finite-time cluster synchronization problem of the neutral-type coupled neural networks (NCNNs) with mixed delays. Compared with the traditional neural networks, the model of NCNNs is more general in some sense, due to that it involves state delays, distributed d...
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| Published in | Neurocomputing (Amsterdam) Vol. 384; pp. 11 - 20 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
07.04.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-2312 1872-8286 |
| DOI | 10.1016/j.neucom.2019.11.046 |
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| Abstract | This paper investigates the adaptive finite-time cluster synchronization problem of the neutral-type coupled neural networks (NCNNs) with mixed delays. Compared with the traditional neural networks, the model of NCNNs is more general in some sense, due to that it involves state delays, distributed delays and coupling delays. In this paper, a novel, adaptive and closed-loop control control algorithm is proposed to achieve the finite-time cluster synchronization of NCNNs with mixed delays. In addition, the sufficient conditions on the control parameters for stabilizing the closed-loop system are derived by leveraging the Lyapunov stability argument. Finally, the simulation results are carried out to illustrate the validity and feasibility of the proposed algorithm. |
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| AbstractList | This paper investigates the adaptive finite-time cluster synchronization problem of the neutral-type coupled neural networks (NCNNs) with mixed delays. Compared with the traditional neural networks, the model of NCNNs is more general in some sense, due to that it involves state delays, distributed delays and coupling delays. In this paper, a novel, adaptive and closed-loop control control algorithm is proposed to achieve the finite-time cluster synchronization of NCNNs with mixed delays. In addition, the sufficient conditions on the control parameters for stabilizing the closed-loop system are derived by leveraging the Lyapunov stability argument. Finally, the simulation results are carried out to illustrate the validity and feasibility of the proposed algorithm. |
| Author | Lin, Ya-Qi Ge, Ming-Feng He, Juan-Juan Ding, Teng-Fei Wang, Leimin Liang, Chang-Duo |
| Author_xml | – sequence: 1 givenname: Juan-Juan surname: He fullname: He, Juan-Juan email: hejuanjuan@wust.edu.cn organization: College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430081, China – sequence: 2 givenname: Ya-Qi surname: Lin fullname: Lin, Ya-Qi email: yqlin0566@163.com organization: College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430081, China – sequence: 3 givenname: Ming-Feng orcidid: 0000-0002-6828-0147 surname: Ge fullname: Ge, Ming-Feng email: fmgabc@163.com, gemf@cug.edu.cn organization: School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China – sequence: 4 givenname: Chang-Duo surname: Liang fullname: Liang, Chang-Duo email: liangchangduo93@163.com organization: School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China – sequence: 5 givenname: Teng-Fei surname: Ding fullname: Ding, Teng-Fei email: dingtf@cug.edu.cn organization: School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China – sequence: 6 givenname: Leimin orcidid: 0000-0002-0663-3365 surname: Wang fullname: Wang, Leimin email: wangleimin@cug.edu.cn organization: School of Automation, China University of Geosciences, Wuhan 430074, China |
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| Keywords | Neutral-type coupled neural networks (NCNNs) Mixed delays Finite-time cluster synchronization Adaptive control |
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| SubjectTerms | Adaptive control Finite-time cluster synchronization Mixed delays Neutral-type coupled neural networks (NCNNs) |
| Title | Adaptive finite-time cluster synchronization of neutral-type coupled neural networks with mixed delays |
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