New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays
In this work, we are concerned with the finite-time synchronization (FTS) control issue of the drive and response delayed memristor-based inertial neural networks (MINNs). Firstly, a novel finite-time stability lemma is developed, which is different from the existing finite-time stability criteria a...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/3/684 |
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| author | Jun Wang Yongqiang Tian Lanfeng Hua Kaibo Shi Shouming Zhong Shiping Wen |
| author_facet | Jun Wang Yongqiang Tian Lanfeng Hua Kaibo Shi Shouming Zhong Shiping Wen |
| author_sort | Jun Wang |
| collection | DOAJ |
| description | In this work, we are concerned with the finite-time synchronization (FTS) control issue of the drive and response delayed memristor-based inertial neural networks (MINNs). Firstly, a novel finite-time stability lemma is developed, which is different from the existing finite-time stability criteria and extends the previous results. Secondly, by constructing an appropriate Lyapunov function, designing effective delay-dependent feedback controllers and combining the finite-time control theory with a new non-reduced order method (NROD), several novel theoretical criteria to ensure the FTS for the studied MINNs are provided. In addition, the obtained theoretical results are established in a more general framework than the previous works and widen the application scope. Lastly, we illustrate the practicality and validity of the theoretical results via some numerical examples. |
| first_indexed | 2024-03-11T09:34:21Z |
| format | Article |
| id | doaj.art-58c765c1ebc740ea838a0f35d1e2821f |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T09:34:21Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-58c765c1ebc740ea838a0f35d1e2821f2023-11-16T17:23:07ZengMDPI AGMathematics2227-73902023-01-0111368410.3390/math11030684New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying DelaysJun Wang0Yongqiang Tian1Lanfeng Hua2Kaibo Shi3Shouming Zhong4Shiping Wen5College of Electrical and Information Engineering, Southwest Minzu University, Chengdu 610041, ChinaHuawei Technologies Co., Ltd., Chengdu 611700, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Electronic Information and Electrical Engineering, Chengdu University, Chengdu 610106, ChinaSchool of Mathematics Sciences, University of Electronic Science and Technology of China, Chengdu 611731, ChinaFaculty of Engineering and Information Technology, Australian AI Institute, University of Technology Sydney, Ultimo, NSW 2007, AustraliaIn this work, we are concerned with the finite-time synchronization (FTS) control issue of the drive and response delayed memristor-based inertial neural networks (MINNs). Firstly, a novel finite-time stability lemma is developed, which is different from the existing finite-time stability criteria and extends the previous results. Secondly, by constructing an appropriate Lyapunov function, designing effective delay-dependent feedback controllers and combining the finite-time control theory with a new non-reduced order method (NROD), several novel theoretical criteria to ensure the FTS for the studied MINNs are provided. In addition, the obtained theoretical results are established in a more general framework than the previous works and widen the application scope. Lastly, we illustrate the practicality and validity of the theoretical results via some numerical examples.https://www.mdpi.com/2227-7390/11/3/684novel finite-time stability theoremsgeneralized MINNsmixed time-varying delaysnew non-reduced order method |
| spellingShingle | Jun Wang Yongqiang Tian Lanfeng Hua Kaibo Shi Shouming Zhong Shiping Wen New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays Mathematics novel finite-time stability theorems generalized MINNs mixed time-varying delays new non-reduced order method |
| title | New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays |
| title_full | New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays |
| title_fullStr | New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays |
| title_full_unstemmed | New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays |
| title_short | New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays |
| title_sort | new results on finite time synchronization control of chaotic memristor based inertial neural networks with time varying delays |
| topic | novel finite-time stability theorems generalized MINNs mixed time-varying delays new non-reduced order method |
| url | https://www.mdpi.com/2227-7390/11/3/684 |
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