Finite-Time and Fixed-Time Synchronization of Inertial Cohen–Grossberg-Type Neural Networks with Time Varying Delays
Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by u...
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| Autor*in: |
Aouiti, Chaouki [verfasserIn] |
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Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Neural processing letters - Springer US, 1994, 50(2019), 3 vom: 11. März, Seite 2407-2436 |
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| Übergeordnetes Werk: |
volume:50 ; year:2019 ; number:3 ; day:11 ; month:03 ; pages:2407-2436 |
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10.1007/s11063-019-10018-8 |
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OLC2044714965 |
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| 520 | |a Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. | ||
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10.1007/s11063-019-10018-8 doi (DE-627)OLC2044714965 (DE-He213)s11063-019-10018-8-p DE-627 ger DE-627 rakwb eng 000 VZ Aouiti, Chaouki verfasserin (orcid)0000-0002-8252-9017 aut Finite-Time and Fixed-Time Synchronization of Inertial Cohen–Grossberg-Type Neural Networks with Time Varying Delays 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. Inertial Cohen–Grossberg-type Neural networks Finite-time synchronization Fixed-time synchronization Time-varying delays Assali, El Abed aut Foutayeni, Youssef El aut Enthalten in Neural processing letters Springer US, 1994 50(2019), 3 vom: 11. März, Seite 2407-2436 (DE-627)198692617 (DE-600)1316823-X (DE-576)052842762 1370-4621 nnns volume:50 year:2019 number:3 day:11 month:03 pages:2407-2436 https://doi.org/10.1007/s11063-019-10018-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PSY SSG-OLC-MAT GBV_ILN_70 AR 50 2019 3 11 03 2407-2436 |
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10.1007/s11063-019-10018-8 doi (DE-627)OLC2044714965 (DE-He213)s11063-019-10018-8-p DE-627 ger DE-627 rakwb eng 000 VZ Aouiti, Chaouki verfasserin (orcid)0000-0002-8252-9017 aut Finite-Time and Fixed-Time Synchronization of Inertial Cohen–Grossberg-Type Neural Networks with Time Varying Delays 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. Inertial Cohen–Grossberg-type Neural networks Finite-time synchronization Fixed-time synchronization Time-varying delays Assali, El Abed aut Foutayeni, Youssef El aut Enthalten in Neural processing letters Springer US, 1994 50(2019), 3 vom: 11. März, Seite 2407-2436 (DE-627)198692617 (DE-600)1316823-X (DE-576)052842762 1370-4621 nnns volume:50 year:2019 number:3 day:11 month:03 pages:2407-2436 https://doi.org/10.1007/s11063-019-10018-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PSY SSG-OLC-MAT GBV_ILN_70 AR 50 2019 3 11 03 2407-2436 |
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10.1007/s11063-019-10018-8 doi (DE-627)OLC2044714965 (DE-He213)s11063-019-10018-8-p DE-627 ger DE-627 rakwb eng 000 VZ Aouiti, Chaouki verfasserin (orcid)0000-0002-8252-9017 aut Finite-Time and Fixed-Time Synchronization of Inertial Cohen–Grossberg-Type Neural Networks with Time Varying Delays 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. Inertial Cohen–Grossberg-type Neural networks Finite-time synchronization Fixed-time synchronization Time-varying delays Assali, El Abed aut Foutayeni, Youssef El aut Enthalten in Neural processing letters Springer US, 1994 50(2019), 3 vom: 11. März, Seite 2407-2436 (DE-627)198692617 (DE-600)1316823-X (DE-576)052842762 1370-4621 nnns volume:50 year:2019 number:3 day:11 month:03 pages:2407-2436 https://doi.org/10.1007/s11063-019-10018-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PSY SSG-OLC-MAT GBV_ILN_70 AR 50 2019 3 11 03 2407-2436 |
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10.1007/s11063-019-10018-8 doi (DE-627)OLC2044714965 (DE-He213)s11063-019-10018-8-p DE-627 ger DE-627 rakwb eng 000 VZ Aouiti, Chaouki verfasserin (orcid)0000-0002-8252-9017 aut Finite-Time and Fixed-Time Synchronization of Inertial Cohen–Grossberg-Type Neural Networks with Time Varying Delays 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. Inertial Cohen–Grossberg-type Neural networks Finite-time synchronization Fixed-time synchronization Time-varying delays Assali, El Abed aut Foutayeni, Youssef El aut Enthalten in Neural processing letters Springer US, 1994 50(2019), 3 vom: 11. März, Seite 2407-2436 (DE-627)198692617 (DE-600)1316823-X (DE-576)052842762 1370-4621 nnns volume:50 year:2019 number:3 day:11 month:03 pages:2407-2436 https://doi.org/10.1007/s11063-019-10018-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PSY SSG-OLC-MAT GBV_ILN_70 AR 50 2019 3 11 03 2407-2436 |
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10.1007/s11063-019-10018-8 doi (DE-627)OLC2044714965 (DE-He213)s11063-019-10018-8-p DE-627 ger DE-627 rakwb eng 000 VZ Aouiti, Chaouki verfasserin (orcid)0000-0002-8252-9017 aut Finite-Time and Fixed-Time Synchronization of Inertial Cohen–Grossberg-Type Neural Networks with Time Varying Delays 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. Inertial Cohen–Grossberg-type Neural networks Finite-time synchronization Fixed-time synchronization Time-varying delays Assali, El Abed aut Foutayeni, Youssef El aut Enthalten in Neural processing letters Springer US, 1994 50(2019), 3 vom: 11. März, Seite 2407-2436 (DE-627)198692617 (DE-600)1316823-X (DE-576)052842762 1370-4621 nnns volume:50 year:2019 number:3 day:11 month:03 pages:2407-2436 https://doi.org/10.1007/s11063-019-10018-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PSY SSG-OLC-MAT GBV_ILN_70 AR 50 2019 3 11 03 2407-2436 |
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Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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Abstract This paper is devoted to studying the finite-time and fixed-time of inertial Cohen–Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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Assali, El Abed Foutayeni, Youssef El |
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Assali, El Abed Foutayeni, Youssef El |
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198692617 |
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| doi_str |
10.1007/s11063-019-10018-8 |
| up_date |
2024-07-04T00:31:56.519Z |
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1803606416707026944 |
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