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Event-Triggered Synchronization of Multiple Discrete-Time Markovian Jump Memristor- Based Neural Networks With Mixed Mode-Dependent Delays.

Authors :
Li, Huiyuan
Fang, Jian-An
Li, Xiaofan
Rutkowski, Leszek
Huang, Tingwen
Source :
IEEE Transactions on Circuits & Systems. Part I: Regular Papers. May2022, Vol. 69 Issue 5, p2095-2107. 13p.
Publication Year :
2022

Abstract

This paper deals with global synchronization problem of multiple discrete-time Markovian jump memristor-based neural networks (DTMJMNNs) with mixed mode-dependent delays via a novel event-triggered impulsive coupling control (ETICC). The parameters of the multiple DTMJMNNs and the mixed time delays (both discrete and distributed delays) switch randomly according to a Markov chain. In the ETICC strategy, the controller does not work all the time, but only works at impulse instants determined by specific events. In particular, the coupling matrix can be non-Laplacian. By using the Lyapunov stability theory, linear matrix inequalities (LMIs), and the Kronecker product, some sufficient conditions for global synchronization of multiple DTMJMNNs under the event-triggered strategy are derived. Two examples are presented to test the validity of the theoretical analysis results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15498328
Volume :
69
Issue :
5
Database :
Academic Search Index
Journal :
IEEE Transactions on Circuits & Systems. Part I: Regular Papers
Publication Type :
Periodical
Accession number :
156630308
Full Text :
https://doi.org/10.1109/TCSI.2022.3149535