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Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays
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| Zeitschriftentitel: | Journal of Artificial Intelligence and Soft Computing Research |
|---|---|
| Personen und Körperschaften: | , |
| In: | Journal of Artificial Intelligence and Soft Computing Research, 8, 2018, 4, S. 269-282 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Walter de Gruyter GmbH
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| Schlagwörter: |
| author_facet |
Wei, Ruoyu Cao, Jinde Wei, Ruoyu Cao, Jinde |
|---|---|
| author |
Wei, Ruoyu Cao, Jinde |
| spellingShingle |
Wei, Ruoyu Cao, Jinde Journal of Artificial Intelligence and Soft Computing Research Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems |
| author_sort |
wei, ruoyu |
| spelling |
Wei, Ruoyu Cao, Jinde 2083-2567 Walter de Gruyter GmbH Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems http://dx.doi.org/10.1515/jaiscr-2018-0017 <jats:title>Abstract</jats:title> <jats:p> This paper investigates the global exponential synchronization and quasi-synchronization of inertial memristive neural networks with time-varying delays. By using a variable transmission, the original second-order system can be transformed into first-order differential system. Then, two types of drive-response systems of inertial memristive neural networks are studied, one is the system with parameter mismatch, the other is the system with matched parameters. By constructing Lyapunov functional and designing feedback controllers, several sufficient conditions are derived respectively for the synchronization of these two types of drive-response systems. Finally, corresponding simulation results are given to show the effectiveness of the proposed method derived in this paper.</jats:p> Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays Journal of Artificial Intelligence and Soft Computing Research |
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Walter de Gruyter GmbH, 2018 |
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Journal of Artificial Intelligence and Soft Computing Research |
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| title |
Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_unstemmed |
Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_full |
Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_fullStr |
Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_full_unstemmed |
Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_short |
Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_sort |
synchronization analysis of inertial memristive neural networks with time-varying delays |
| topic |
Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems |
| url |
http://dx.doi.org/10.1515/jaiscr-2018-0017 |
| publishDate |
2018 |
| physical |
269-282 |
| description |
<jats:title>Abstract</jats:title>
<jats:p> This paper investigates the global exponential synchronization and quasi-synchronization of inertial memristive neural networks with time-varying delays. By using a variable transmission, the original second-order system can be transformed into first-order differential system. Then, two types of drive-response systems of inertial memristive neural networks are studied, one is the system with parameter mismatch, the other is the system with matched parameters. By constructing Lyapunov functional and designing feedback controllers, several sufficient conditions are derived respectively for the synchronization of these two types of drive-response systems. Finally, corresponding simulation results are given to show the effectiveness of the proposed method derived in this paper.</jats:p> |
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| container_title | Journal of Artificial Intelligence and Soft Computing Research |
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| description | <jats:title>Abstract</jats:title> <jats:p> This paper investigates the global exponential synchronization and quasi-synchronization of inertial memristive neural networks with time-varying delays. By using a variable transmission, the original second-order system can be transformed into first-order differential system. Then, two types of drive-response systems of inertial memristive neural networks are studied, one is the system with parameter mismatch, the other is the system with matched parameters. By constructing Lyapunov functional and designing feedback controllers, several sufficient conditions are derived respectively for the synchronization of these two types of drive-response systems. Finally, corresponding simulation results are given to show the effectiveness of the proposed method derived in this paper.</jats:p> |
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| imprint | Walter de Gruyter GmbH, 2018 |
| imprint_str_mv | Walter de Gruyter GmbH, 2018 |
| institution | DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161 |
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| physical | 269-282 |
| publishDate | 2018 |
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| series | Journal of Artificial Intelligence and Soft Computing Research |
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| spelling | Wei, Ruoyu Cao, Jinde 2083-2567 Walter de Gruyter GmbH Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems http://dx.doi.org/10.1515/jaiscr-2018-0017 <jats:title>Abstract</jats:title> <jats:p> This paper investigates the global exponential synchronization and quasi-synchronization of inertial memristive neural networks with time-varying delays. By using a variable transmission, the original second-order system can be transformed into first-order differential system. Then, two types of drive-response systems of inertial memristive neural networks are studied, one is the system with parameter mismatch, the other is the system with matched parameters. By constructing Lyapunov functional and designing feedback controllers, several sufficient conditions are derived respectively for the synchronization of these two types of drive-response systems. Finally, corresponding simulation results are given to show the effectiveness of the proposed method derived in this paper.</jats:p> Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays Journal of Artificial Intelligence and Soft Computing Research |
| spellingShingle | Wei, Ruoyu, Cao, Jinde, Journal of Artificial Intelligence and Soft Computing Research, Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays, Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Modeling and Simulation, Information Systems |
| title | Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_full | Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_fullStr | Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_full_unstemmed | Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_short | Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| title_sort | synchronization analysis of inertial memristive neural networks with time-varying delays |
| title_unstemmed | Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays |
| topic | Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Modeling and Simulation, Information Systems |
| url | http://dx.doi.org/10.1515/jaiscr-2018-0017 |