Stability property of impulsive inertial neural networks with unbounded time delay and saturating actuators
Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks....
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ouyang, Deqiang [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Ltd., part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Neural computing & applications - Springer London, 1993, 32(2019), 11 vom: 06. März, Seite 6571-6580 |
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| Übergeordnetes Werk: |
volume:32 ; year:2019 ; number:11 ; day:06 ; month:03 ; pages:6571-6580 |
| Links: |
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| DOI / URN: |
10.1007/s00521-019-04115-x |
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OLC2025621035 |
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| 520 | |a Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. | ||
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10.1007/s00521-019-04115-x doi (DE-627)OLC2025621035 (DE-He213)s00521-019-04115-x-p DE-627 ger DE-627 rakwb eng 004 VZ Ouyang, Deqiang verfasserin aut Stability property of impulsive inertial neural networks with unbounded time delay and saturating actuators 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. Stability property Unbounded delay Impulsive effect Inertial neural networks Saturating actuators Shao, Jie (orcid)0000-0003-2615-1555 aut Hu, Cheng aut Enthalten in Neural computing & applications Springer London, 1993 32(2019), 11 vom: 06. März, Seite 6571-6580 (DE-627)165669608 (DE-600)1136944-9 (DE-576)032873050 0941-0643 nnns volume:32 year:2019 number:11 day:06 month:03 pages:6571-6580 https://doi.org/10.1007/s00521-019-04115-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 32 2019 11 06 03 6571-6580 |
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10.1007/s00521-019-04115-x doi (DE-627)OLC2025621035 (DE-He213)s00521-019-04115-x-p DE-627 ger DE-627 rakwb eng 004 VZ Ouyang, Deqiang verfasserin aut Stability property of impulsive inertial neural networks with unbounded time delay and saturating actuators 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. Stability property Unbounded delay Impulsive effect Inertial neural networks Saturating actuators Shao, Jie (orcid)0000-0003-2615-1555 aut Hu, Cheng aut Enthalten in Neural computing & applications Springer London, 1993 32(2019), 11 vom: 06. März, Seite 6571-6580 (DE-627)165669608 (DE-600)1136944-9 (DE-576)032873050 0941-0643 nnns volume:32 year:2019 number:11 day:06 month:03 pages:6571-6580 https://doi.org/10.1007/s00521-019-04115-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 32 2019 11 06 03 6571-6580 |
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10.1007/s00521-019-04115-x doi (DE-627)OLC2025621035 (DE-He213)s00521-019-04115-x-p DE-627 ger DE-627 rakwb eng 004 VZ Ouyang, Deqiang verfasserin aut Stability property of impulsive inertial neural networks with unbounded time delay and saturating actuators 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. Stability property Unbounded delay Impulsive effect Inertial neural networks Saturating actuators Shao, Jie (orcid)0000-0003-2615-1555 aut Hu, Cheng aut Enthalten in Neural computing & applications Springer London, 1993 32(2019), 11 vom: 06. März, Seite 6571-6580 (DE-627)165669608 (DE-600)1136944-9 (DE-576)032873050 0941-0643 nnns volume:32 year:2019 number:11 day:06 month:03 pages:6571-6580 https://doi.org/10.1007/s00521-019-04115-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 32 2019 11 06 03 6571-6580 |
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10.1007/s00521-019-04115-x doi (DE-627)OLC2025621035 (DE-He213)s00521-019-04115-x-p DE-627 ger DE-627 rakwb eng 004 VZ Ouyang, Deqiang verfasserin aut Stability property of impulsive inertial neural networks with unbounded time delay and saturating actuators 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. Stability property Unbounded delay Impulsive effect Inertial neural networks Saturating actuators Shao, Jie (orcid)0000-0003-2615-1555 aut Hu, Cheng aut Enthalten in Neural computing & applications Springer London, 1993 32(2019), 11 vom: 06. März, Seite 6571-6580 (DE-627)165669608 (DE-600)1136944-9 (DE-576)032873050 0941-0643 nnns volume:32 year:2019 number:11 day:06 month:03 pages:6571-6580 https://doi.org/10.1007/s00521-019-04115-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 32 2019 11 06 03 6571-6580 |
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Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2025621035</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504150742.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2019 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00521-019-04115-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2025621035</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00521-019-04115-x-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ouyang, Deqiang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Stability property of impulsive inertial neural networks with unbounded time delay and saturating actuators</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag London Ltd., part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper considers the stability property of impulsive inertial neural networks with unbounded delay and saturating actuators. Based on polytopic representation approach, some sufficient conditions to ensure global asymptotic stability are obtained for impulsive inertial neural networks. By using Lyapunov function with the matrix form of 2-norm, we obtain some conditions to ensure the stability of impulsive inertial neural networks. Finally, the validity of this method is verified by several simulation examples.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Stability property</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Unbounded delay</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Impulsive effect</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Inertial neural networks</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Saturating actuators</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shao, Jie</subfield><subfield code="0">(orcid)0000-0003-2615-1555</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hu, Cheng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Neural computing & applications</subfield><subfield code="d">Springer London, 1993</subfield><subfield code="g">32(2019), 11 vom: 06. 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