Finite/fixed-time synchronization control of coupled memristive neural networks
Finite-time and fixed-time synchronization (FAFS) of coupled memristive neural networks (CMNNs) with discontinuous feedback functions are explored in this paper. Firstly, a more comprehensive stability theory is systematically established. Secondly, by designing adaptive feedback controller and disc...
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| Published in | Journal of the Franklin Institute Vol. 356; no. 16; pp. 9928 - 9952 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elmsford
Elsevier Ltd
01.11.2019
Elsevier Science Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0016-0032 1879-2693 0016-0032 |
| DOI | 10.1016/j.jfranklin.2019.09.015 |
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| Abstract | Finite-time and fixed-time synchronization (FAFS) of coupled memristive neural networks (CMNNs) with discontinuous feedback functions are explored in this paper. Firstly, a more comprehensive stability theory is systematically established. Secondly, by designing adaptive feedback controller and discontinuous feedback controller, both finite-time and fixed-time synchronization can be realized through regulating the main control parameter. Thirdly, 1-norm and quadratic-norm Lyapunov functions are considered simultaneously in this article, while in estimating the settling time, the former one is more accurate than the latter one under the same synchronization criteria. Finally, in numerical simulation, the analysis and comparison of the proposed controllers are given to show the effectiveness of the corresponding results. |
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| AbstractList | Finite-time and fixed-time synchronization (FAFS) of coupled memristive neural networks (CMNNs) with discontinuous feedback functions are explored in this paper. Firstly, a more comprehensive stability theory is systematically established. Secondly, by designing adaptive feedback controller and discontinuous feedback controller, both finite-time and fixed-time synchronization can be realized through regulating the main control parameter. Thirdly, 1-norm and quadratic-norm Lyapunov functions are considered simultaneously in this article, while in estimating the settling time, the former one is more accurate than the latter one under the same synchronization criteria. Finally, in numerical simulation, the analysis and comparison of the proposed controllers are given to show the effectiveness of the corresponding results. |
| Author | Jiang, Haijun Li, Jiarong Hu, Cheng Alsaedi, Ahmed |
| Author_xml | – sequence: 1 givenname: Jiarong surname: Li fullname: Li, Jiarong organization: College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, Xinjiang, China – sequence: 2 givenname: Haijun surname: Jiang fullname: Jiang, Haijun email: jianghaijunxj@sina.com, jianghai@xju.edu.cn organization: College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, Xinjiang, China – sequence: 3 givenname: Cheng orcidid: 0000-0002-2170-0968 surname: Hu fullname: Hu, Cheng organization: College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, Xinjiang, China – sequence: 4 givenname: Ahmed surname: Alsaedi fullname: Alsaedi, Ahmed organization: Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia |
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| SubjectTerms | Computer simulation Control stability Control systems design Feedback control Feedback control systems Finite element analysis Liapunov functions Neural networks Time synchronization |
| Title | Finite/fixed-time synchronization control of coupled memristive neural networks |
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