Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays

This paper addresses finite-time projective synchronization of stochastic complex-valued neural networks (SCVNNs) with probabilistic time-varying delays (PTVs). First, in the complex domain, PTVs are introduced into the studied model and a novel feedback control scheme is constructed. Next, based on...

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Main Authors:	Meng Hui, Jiahuang Zhang, Jiao Zhang, Herbert Ho-Ching Iu, Rui Yao, Lin Bai
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Series:	IEEE Access
Subjects:	Projective synchronization finite-time probabilistic time-varying delays stochastic complex-valued neural networks
Online Access:	https://ieeexplore.ieee.org/document/9380365/

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spelling	doaj-6217f82c3bcd4fe2a5b3baead9ac51f52021-03-30T15:27:07ZengIEEEIEEE Access2169-35362021-01-019447844479610.1109/ACCESS.2021.30665859380365Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying DelaysMeng Hui0https://orcid.org/0000-0002-0468-7335Jiahuang Zhang1https://orcid.org/0000-0001-7159-908XJiao Zhang2Herbert Ho-Ching Iu3https://orcid.org/0000-0002-0687-4038Rui Yao4Lin Bai5School of Electronic and Control, Chang’an University, Xi’an, ChinaSchool of Electronic and Control, Chang’an University, Xi’an, ChinaSchool of Electrical Engineering, Xi’an Jiaotong University, Xi’an, ChinaSchool of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA~, AustraliaSchool of Electronic and Control, Chang’an University, Xi’an, ChinaSchool of Electronic and Control, Chang’an University, Xi’an, ChinaThis paper addresses finite-time projective synchronization of stochastic complex-valued neural networks (SCVNNs) with probabilistic time-varying delays (PTVs). First, in the complex domain, PTVs are introduced into the studied model and a novel feedback control scheme is constructed. Next, based on inequalities techniques and the Lyapunov stability approach, some novel projective synchronization criteria are established by decomposing SCVNNs into two equivalent real-valued systems. Moreover, a setting time function is created by employing lemma 4. Compared with previous researches, our theory content is an extension and complement to known results. Finally, numerical simulation is presented to validate the effectiveness of theoretical analysis results.https://ieeexplore.ieee.org/document/9380365/Projective synchronizationfinite-timeprobabilistic time-varying delaysstochastic complex-valued neural networks
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Meng Hui Jiahuang Zhang Jiao Zhang Herbert Ho-Ching Iu Rui Yao Lin Bai
spellingShingle	Meng Hui Jiahuang Zhang Jiao Zhang Herbert Ho-Ching Iu Rui Yao Lin Bai Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays IEEE Access Projective synchronization finite-time probabilistic time-varying delays stochastic complex-valued neural networks
author_facet	Meng Hui Jiahuang Zhang Jiao Zhang Herbert Ho-Ching Iu Rui Yao Lin Bai
author_sort	Meng Hui
title	Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays
title_short	Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays
title_full	Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays
title_fullStr	Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays
title_full_unstemmed	Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays
title_sort	finite-time projective synchronization of stochastic complex-valued neural networks with probabilistic time-varying delays
publisher	IEEE
series	IEEE Access
issn	2169-3536
publishDate	2021-01-01
description	This paper addresses finite-time projective synchronization of stochastic complex-valued neural networks (SCVNNs) with probabilistic time-varying delays (PTVs). First, in the complex domain, PTVs are introduced into the studied model and a novel feedback control scheme is constructed. Next, based on inequalities techniques and the Lyapunov stability approach, some novel projective synchronization criteria are established by decomposing SCVNNs into two equivalent real-valued systems. Moreover, a setting time function is created by employing lemma 4. Compared with previous researches, our theory content is an extension and complement to known results. Finally, numerical simulation is presented to validate the effectiveness of theoretical analysis results.
topic	Projective synchronization finite-time probabilistic time-varying delays stochastic complex-valued neural networks
url	https://ieeexplore.ieee.org/document/9380365/
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Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays

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