Global exponential synchronization of quaternion-valued memristive neural networks with time delays

This paper extends the memristive neural networks (MNNs) to quaternion field, a new class of neural networks named quaternion-valued memristive neural networks (QVMNNs) is then established, and the problem of drive-response global synchronization of this type of networks is investigated in this pape...

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Main Authors: Ruoyu Wei, Jinde Cao
Format: Article
Language:English
Published: Vilnius University Press 2020-01-01
Series:Nonlinear Analysis
Subjects:
Online Access:https://www.zurnalai.vu.lt/nonlinear-analysis/article/view/15724
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author Ruoyu Wei
Jinde Cao
author_facet Ruoyu Wei
Jinde Cao
author_sort Ruoyu Wei
collection DOAJ
description This paper extends the memristive neural networks (MNNs) to quaternion field, a new class of neural networks named quaternion-valued memristive neural networks (QVMNNs) is then established, and the problem of drive-response global synchronization of this type of networks is investigated in this paper. Two cases are taken into consideration: one is with the conventional differential inclusion assumption, the other without. Criteria for the global synchronization of these two cases are achieved respectively by appropriately choosing the Lyapunov functional and applying some inequality techniques. Finally, corresponding simulation examples are presented to demonstrate the correctness of the proposed results derived in this paper.
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spelling doaj.art-c2726e473bd146f39a5d0e5add9de71c2022-12-21T19:15:27ZengVilnius University PressNonlinear Analysis1392-51132335-89632020-01-0125110.15388/namc.2020.25.15724Global exponential synchronization of quaternion-valued memristive neural networks with time delaysRuoyu Wei0Jinde Cao1Southeast UniversitySoutheast UniversityThis paper extends the memristive neural networks (MNNs) to quaternion field, a new class of neural networks named quaternion-valued memristive neural networks (QVMNNs) is then established, and the problem of drive-response global synchronization of this type of networks is investigated in this paper. Two cases are taken into consideration: one is with the conventional differential inclusion assumption, the other without. Criteria for the global synchronization of these two cases are achieved respectively by appropriately choosing the Lyapunov functional and applying some inequality techniques. Finally, corresponding simulation examples are presented to demonstrate the correctness of the proposed results derived in this paper.https://www.zurnalai.vu.lt/nonlinear-analysis/article/view/15724memristorexponential synchronizationdrive-response systemsquaterniontime delay
spellingShingle Ruoyu Wei
Jinde Cao
Global exponential synchronization of quaternion-valued memristive neural networks with time delays
Nonlinear Analysis
memristor
exponential synchronization
drive-response systems
quaternion
time delay
title Global exponential synchronization of quaternion-valued memristive neural networks with time delays
title_full Global exponential synchronization of quaternion-valued memristive neural networks with time delays
title_fullStr Global exponential synchronization of quaternion-valued memristive neural networks with time delays
title_full_unstemmed Global exponential synchronization of quaternion-valued memristive neural networks with time delays
title_short Global exponential synchronization of quaternion-valued memristive neural networks with time delays
title_sort global exponential synchronization of quaternion valued memristive neural networks with time delays
topic memristor
exponential synchronization
drive-response systems
quaternion
time delay
url https://www.zurnalai.vu.lt/nonlinear-analysis/article/view/15724
work_keys_str_mv AT ruoyuwei globalexponentialsynchronizationofquaternionvaluedmemristiveneuralnetworkswithtimedelays
AT jindecao globalexponentialsynchronizationofquaternionvaluedmemristiveneuralnetworkswithtimedelays