Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme

Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme

This paper studies the modeling and exponential stability problems for markovian jumping memristor-based neural networks (MJMNNs) via event-triggered impulsive control scheme (ETICS). The purpose is to design memristor-based neural networks (MNNs) which has markovian jumping parameters and hybrid ti...

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Main Authors: Nijing Yang, Yongbin Yu, Shouming Zhong, Xiangxiang Wang, Kaibo Shi, Jingye Cai
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Memristor-based neural networks
Markovian jumping
event-triggered impulsive control scheme
exponential stability
Online Access:https://ieeexplore.ieee.org/document/8999520/
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spelling doaj-af8593fa5d1a48f383839a006ee4cd2d2021-03-30T01:29:15ZengIEEEIEEE Access2169-35362020-01-018325643257410.1109/ACCESS.2020.29740408999520Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control SchemeNijing Yang0https://orcid.org/0000-0001-5553-0031Yongbin Yu1https://orcid.org/0000-0001-6022-7504Shouming Zhong2https://orcid.org/0000-0002-0334-6117Xiangxiang Wang3https://orcid.org/0000-0001-9341-1068Kaibo Shi4https://orcid.org/0000-0002-9863-9229Jingye Cai5https://orcid.org/0000-0001-6892-3918School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Mathematical Science, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information Science and Engineering, Chengdu University, Chengdu, ChinaSchool of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaThis paper studies the modeling and exponential stability problems for markovian jumping memristor-based neural networks (MJMNNs) via event-triggered impulsive control scheme (ETICS). The purpose is to design memristor-based neural networks (MNNs) which has markovian jumping parameters and hybrid time-vary delays to make the MNNs more general. Meanwhile, a state estimator is introduced to estimate system states through a vailable output measurements. Furthermore, the proposed event-triggered scheme (ETS), which is also determined by markovian parameters, is used to determine whether there is an impulse and whether the system need to transmit the sampled state information. Then, by using Lyapunov-Krasovskii functional (LKF) and an improved inequality, exponential stable criterions are established. Finally, a numerical example is given to support the results.https://ieeexplore.ieee.org/document/8999520/Memristor-based neural networksMarkovian jumpingevent-triggered impulsive control schemeexponential stability
collection DOAJ
language English
format Article
sources DOAJ
author Nijing Yang
Yongbin Yu
Shouming Zhong
Xiangxiang Wang
Kaibo Shi
Jingye Cai
spellingShingle Nijing Yang
Yongbin Yu
Shouming Zhong
Xiangxiang Wang
Kaibo Shi
Jingye Cai
Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme
IEEE Access
Memristor-based neural networks
Markovian jumping
event-triggered impulsive control scheme
exponential stability
author_facet Nijing Yang
Yongbin Yu
Shouming Zhong
Xiangxiang Wang
Kaibo Shi
Jingye Cai
author_sort Nijing Yang
title Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme
title_short Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme
title_full Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme
title_fullStr Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme
title_full_unstemmed Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme
title_sort exponential stability of markovian jumping memristor-based neural networks via event-triggered impulsive control scheme
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description This paper studies the modeling and exponential stability problems for markovian jumping memristor-based neural networks (MJMNNs) via event-triggered impulsive control scheme (ETICS). The purpose is to design memristor-based neural networks (MNNs) which has markovian jumping parameters and hybrid time-vary delays to make the MNNs more general. Meanwhile, a state estimator is introduced to estimate system states through a vailable output measurements. Furthermore, the proposed event-triggered scheme (ETS), which is also determined by markovian parameters, is used to determine whether there is an impulse and whether the system need to transmit the sampled state information. Then, by using Lyapunov-Krasovskii functional (LKF) and an improved inequality, exponential stable criterions are established. Finally, a numerical example is given to support the results.
topic Memristor-based neural networks
Markovian jumping
event-triggered impulsive control scheme
exponential stability
url https://ieeexplore.ieee.org/document/8999520/
work_keys_str_mv AT nijingyang exponentialstabilityofmarkovianjumpingmemristorbasedneuralnetworksviaeventtriggeredimpulsivecontrolscheme
AT yongbinyu exponentialstabilityofmarkovianjumpingmemristorbasedneuralnetworksviaeventtriggeredimpulsivecontrolscheme
AT shoumingzhong exponentialstabilityofmarkovianjumpingmemristorbasedneuralnetworksviaeventtriggeredimpulsivecontrolscheme
AT xiangxiangwang exponentialstabilityofmarkovianjumpingmemristorbasedneuralnetworksviaeventtriggeredimpulsivecontrolscheme
AT kaiboshi exponentialstabilityofmarkovianjumpingmemristorbasedneuralnetworksviaeventtriggeredimpulsivecontrolscheme
AT jingyecai exponentialstabilityofmarkovianjumpingmemristorbasedneuralnetworksviaeventtriggeredimpulsivecontrolscheme
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