Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks
This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem o...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhang, Ancai [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014transfer abstract |
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| Schlagwörter: |
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| Umfang: |
12 |
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| Übergeordnetes Werk: |
Enthalten in: Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing - 2012, the official journal of the International Neural Network Society, European Neural Network Society and Japanese Neural Network Society, Amsterdam |
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| Übergeordnetes Werk: |
volume:50 ; year:2014 ; pages:98-109 ; extent:12 |
| Links: |
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| DOI / URN: |
10.1016/j.neunet.2013.11.005 |
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ELV034010807 |
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| 520 | |a This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. | ||
| 520 | |a This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. | ||
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10.1016/j.neunet.2013.11.005 doi GBVA2014015000004.pica (DE-627)ELV034010807 (ELSEVIER)S0893-6080(13)00269-4 DE-627 ger DE-627 rakwb eng 004 004 DE-600 620 VZ 610 VZ 77.50 bkl Zhang, Ancai verfasserin aut Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks 2014transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. High-order neural networks Elsevier Bidirectional associative memory (BAM) Elsevier Young’s inequality Elsevier Discrete-time Elsevier Exponential stability Elsevier Qiu, Jianlong oth She, Jinhua oth Enthalten in Elsevier Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing 2012 the official journal of the International Neural Network Society, European Neural Network Society and Japanese Neural Network Society Amsterdam (DE-627)ELV016218965 volume:50 year:2014 pages:98-109 extent:12 https://doi.org/10.1016/j.neunet.2013.11.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 77.50 Psychophysiologie VZ AR 50 2014 98-109 12 045F 004 |
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10.1016/j.neunet.2013.11.005 doi GBVA2014015000004.pica (DE-627)ELV034010807 (ELSEVIER)S0893-6080(13)00269-4 DE-627 ger DE-627 rakwb eng 004 004 DE-600 620 VZ 610 VZ 77.50 bkl Zhang, Ancai verfasserin aut Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks 2014transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. High-order neural networks Elsevier Bidirectional associative memory (BAM) Elsevier Young’s inequality Elsevier Discrete-time Elsevier Exponential stability Elsevier Qiu, Jianlong oth She, Jinhua oth Enthalten in Elsevier Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing 2012 the official journal of the International Neural Network Society, European Neural Network Society and Japanese Neural Network Society Amsterdam (DE-627)ELV016218965 volume:50 year:2014 pages:98-109 extent:12 https://doi.org/10.1016/j.neunet.2013.11.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 77.50 Psychophysiologie VZ AR 50 2014 98-109 12 045F 004 |
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10.1016/j.neunet.2013.11.005 doi GBVA2014015000004.pica (DE-627)ELV034010807 (ELSEVIER)S0893-6080(13)00269-4 DE-627 ger DE-627 rakwb eng 004 004 DE-600 620 VZ 610 VZ 77.50 bkl Zhang, Ancai verfasserin aut Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks 2014transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. High-order neural networks Elsevier Bidirectional associative memory (BAM) Elsevier Young’s inequality Elsevier Discrete-time Elsevier Exponential stability Elsevier Qiu, Jianlong oth She, Jinhua oth Enthalten in Elsevier Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing 2012 the official journal of the International Neural Network Society, European Neural Network Society and Japanese Neural Network Society Amsterdam (DE-627)ELV016218965 volume:50 year:2014 pages:98-109 extent:12 https://doi.org/10.1016/j.neunet.2013.11.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 77.50 Psychophysiologie VZ AR 50 2014 98-109 12 045F 004 |
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10.1016/j.neunet.2013.11.005 doi GBVA2014015000004.pica (DE-627)ELV034010807 (ELSEVIER)S0893-6080(13)00269-4 DE-627 ger DE-627 rakwb eng 004 004 DE-600 620 VZ 610 VZ 77.50 bkl Zhang, Ancai verfasserin aut Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks 2014transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. High-order neural networks Elsevier Bidirectional associative memory (BAM) Elsevier Young’s inequality Elsevier Discrete-time Elsevier Exponential stability Elsevier Qiu, Jianlong oth She, Jinhua oth Enthalten in Elsevier Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing 2012 the official journal of the International Neural Network Society, European Neural Network Society and Japanese Neural Network Society Amsterdam (DE-627)ELV016218965 volume:50 year:2014 pages:98-109 extent:12 https://doi.org/10.1016/j.neunet.2013.11.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 77.50 Psychophysiologie VZ AR 50 2014 98-109 12 045F 004 |
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10.1016/j.neunet.2013.11.005 doi GBVA2014015000004.pica (DE-627)ELV034010807 (ELSEVIER)S0893-6080(13)00269-4 DE-627 ger DE-627 rakwb eng 004 004 DE-600 620 VZ 610 VZ 77.50 bkl Zhang, Ancai verfasserin aut Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks 2014transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. High-order neural networks Elsevier Bidirectional associative memory (BAM) Elsevier Young’s inequality Elsevier Discrete-time Elsevier Exponential stability Elsevier Qiu, Jianlong oth She, Jinhua oth Enthalten in Elsevier Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing 2012 the official journal of the International Neural Network Society, European Neural Network Society and Japanese Neural Network Society Amsterdam (DE-627)ELV016218965 volume:50 year:2014 pages:98-109 extent:12 https://doi.org/10.1016/j.neunet.2013.11.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 77.50 Psychophysiologie VZ AR 50 2014 98-109 12 045F 004 |
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Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks |
| author_sort |
Zhang, Ancai |
| journal |
Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing |
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Regulatory design for RES-E support mechanisms: Learning curves, market structure, and burden-sharing |
| lang_code |
eng |
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000 - Computer science, information & general works 600 - Technology |
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marc |
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2014 |
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98 |
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Zhang, Ancai |
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50 |
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12 |
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004 004 DE-600 620 VZ 610 VZ 77.50 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Zhang, Ancai |
| doi_str_mv |
10.1016/j.neunet.2013.11.005 |
| dewey-full |
004 620 610 |
| title_sort |
existence and global exponential stability of periodic solution for high-order discrete-time bam neural networks |
| title_auth |
Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks |
| abstract |
This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. |
| abstractGer |
This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. |
| abstract_unstemmed |
This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. |
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GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA |
| title_short |
Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks |
| url |
https://doi.org/10.1016/j.neunet.2013.11.005 |
| remote_bool |
true |
| author2 |
Qiu, Jianlong She, Jinhua |
| author2Str |
Qiu, Jianlong She, Jinhua |
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10.1016/j.neunet.2013.11.005 |
| up_date |
2024-07-06T20:02:27.120Z |
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