Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control

Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control

This paper formulates the models of systems of nonlinearly and diffusively coupled memristive neural networks (CMNNs) with time-varying delays and then investigates its dynamic behaviors. Particularly, a simple yet a generic sufficient condition for quasi-synchronization of drive-response CMNNs is d...

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Main Authors: Jianwen Feng, Siya Chen, Jingyi Wang, Yi Zhao
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Quasi-synchronization
memristive neural network
nonlinear coupling
pinning control
Online Access:https://ieeexplore.ieee.org/document/8358695/
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spelling doaj-0e79255455c445e4a7017128a274321a2021-03-29T21:09:35ZengIEEEIEEE Access2169-35362018-01-016262712628210.1109/ACCESS.2018.28361428358695Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning ControlJianwen Feng0Siya Chen1Jingyi Wang2https://orcid.org/0000-0002-0703-0320Yi Zhao3College of Mathematics and Statistics, Shenzhen University, Shenzhen, ChinaCollege of Mathematics and Statistics, Shenzhen University, Shenzhen, ChinaCollege of Mathematics and Statistics, Shenzhen University, Shenzhen, ChinaCollege of Mathematics and Statistics, Shenzhen University, Shenzhen, ChinaThis paper formulates the models of systems of nonlinearly and diffusively coupled memristive neural networks (CMNNs) with time-varying delays and then investigates its dynamic behaviors. Particularly, a simple yet a generic sufficient condition for quasi-synchronization of drive-response CMNNs is derived based on the Lyapunov functional methods and matrix theories. The main result shows that quasi-synchronization of such CMNNs is guaranteed by suitably designing the memsitive mechanism, the coupling matrix, and the pinning control strategy. In addition, some applicable corollaries derived from the main result are drawn by considering other circumstances, such as the linearly coupling functions, the adjustable coupling strengths, the number of controlled nodes, and so on. Finally, some numerical simulations are presented to demonstrate the effectiveness of the results.https://ieeexplore.ieee.org/document/8358695/Quasi-synchronizationmemristive neural networknonlinear couplingpinning control
collection DOAJ
language English
format Article
sources DOAJ
author Jianwen Feng
Siya Chen
Jingyi Wang
Yi Zhao
spellingShingle Jianwen Feng
Siya Chen
Jingyi Wang
Yi Zhao
Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control
IEEE Access
Quasi-synchronization
memristive neural network
nonlinear coupling
pinning control
author_facet Jianwen Feng
Siya Chen
Jingyi Wang
Yi Zhao
author_sort Jianwen Feng
title Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control
title_short Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control
title_full Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control
title_fullStr Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control
title_full_unstemmed Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control
title_sort quasi-synchronization of coupled nonlinear memristive neural networks with time delays by pinning control
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description This paper formulates the models of systems of nonlinearly and diffusively coupled memristive neural networks (CMNNs) with time-varying delays and then investigates its dynamic behaviors. Particularly, a simple yet a generic sufficient condition for quasi-synchronization of drive-response CMNNs is derived based on the Lyapunov functional methods and matrix theories. The main result shows that quasi-synchronization of such CMNNs is guaranteed by suitably designing the memsitive mechanism, the coupling matrix, and the pinning control strategy. In addition, some applicable corollaries derived from the main result are drawn by considering other circumstances, such as the linearly coupling functions, the adjustable coupling strengths, the number of controlled nodes, and so on. Finally, some numerical simulations are presented to demonstrate the effectiveness of the results.
topic Quasi-synchronization
memristive neural network
nonlinear coupling
pinning control
url https://ieeexplore.ieee.org/document/8358695/
work_keys_str_mv AT jianwenfeng quasisynchronizationofcouplednonlinearmemristiveneuralnetworkswithtimedelaysbypinningcontrol
AT siyachen quasisynchronizationofcouplednonlinearmemristiveneuralnetworkswithtimedelaysbypinningcontrol
AT jingyiwang quasisynchronizationofcouplednonlinearmemristiveneuralnetworkswithtimedelaysbypinningcontrol
AT yizhao quasisynchronizationofcouplednonlinearmemristiveneuralnetworkswithtimedelaysbypinningcontrol
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