Master-slave synchronization of neural networks with time-varying delays via the event-triggered control
This paper investigates the problem of master-slave synchronization of neural networks with time-varying delays via the event-triggered control (ETC). First, the proposed ETC can effectively reduce the total amount of data transmitted to the controller in the synchronization process and avoid commun...
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Published in | Mathematical and computer modelling of dynamical systems Vol. 26; no. 4; pp. 357 - 373 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Abingdon
Taylor & Francis
03.07.2020
Taylor & Francis Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | This paper investigates the problem of master-slave synchronization of neural networks with time-varying delays via the event-triggered control (ETC). First, the proposed ETC can effectively reduce the total amount of data transmitted to the controller in the synchronization process and avoid communication channel congestion. Second, a master-slave synchronization of neural networks with time-varying delays is constructed, where delays within neural networks and the ETC are simultaneous existence. The controller is updated by the ETC. By the Lyapunov stability theory, some sufficient criteria are obtained to ensure master-slave synchronization of neural networks. Finally, a numerical example and a tunnel diode circuit example are used to verify the validity of results obtained. |
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ISSN: | 1387-3954 1744-5051 |
DOI: | 10.1080/13873954.2020.1777567 |