Exponential stability of Cohen-Grossberg neural networks with delays and impulses
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作者:
Tang, Qing
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China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R ChinaChina Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China
Tang, Qing
[1
]
Liu, Anping
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China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R ChinaChina Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China
Liu, Anping
[1
]
Li, Huijuan
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China Univ Geosci, State Key Lab Geol Proc & Mineral Resources, Beijing, Peoples R ChinaChina Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China
Li, Huijuan
[2
]
Zou, Min
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China Univ Geosci, State Key Lab Geol Proc & Mineral Resources, Beijing, Peoples R ChinaChina Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China
Zou, Min
[2
]
机构:
[1] China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China
[2] China Univ Geosci, State Key Lab Geol Proc & Mineral Resources, Beijing, Peoples R China
来源:
2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL II, PROCEEDINGS
|
2009年
As an important tool to study practical problems of biology, engineering and image processing, the neural networks has caused more and more attention. Some interesting results on the stability have been obtained. In this paper, the exponential stability of the equilibrium point of a group of Cohen-Grossberg neural networks is obtained by using Lyapunov method and Razumikhin technique.