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Global stability analysis of competitive neural networks with mixed time-varying delays and discontinuous neuron activations

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成果类型:
期刊论文
作者:
Wang, Yanqun;Huang, Lihong*
通讯作者:
Huang, Lihong
作者机构:
[Huang, Lihong; Wang, Yanqun] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China.
[Wang, Yanqun] Hengyang Normal Univ, Dept Math & Comp Sci, Hengyang 421008, Hunan, Peoples R China.
[Huang, Lihong] Hunan Womens Univ, Changsha 410004, Hunan, Peoples R China.
通讯机构:
[Huang, Lihong] H
Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China.
语种:
英文
关键词:
Competitive neural networks;Convergence in finite time;Discontinuous activation;Global exponential stability;Mixed time-varying delays
期刊:
Neurocomputing
ISSN:
0925-2312
年:
2015
卷:
152
页码:
85-96
基金类别:
National Natural Science Foundations of ChinaNational Natural Science Foundation of China (NSFC) [11371127]; Construct Program of the Key Discipline in Hunan Province [(2011)76]; Cultivation of Young Teachers of Hengyang Normal University of China
机构署名:
本校为其他机构
院系归属:
数学与统计学院
摘要:
In this paper, the global stability has been investigated for a novel class of competitive neural networks with mixed time delays and discontinuous activations. Without presuming the boundedness of activation functions, we draw two set of sufficient conditions ensuring the existence, uniqueness of the equilibrium, global exponential asymptotic stability of the solution and the associated output of the solution converging to the output equilibrium point in measure, by linear matrix inequality, M-matrix, Leray-Schauder alternative theorem in multivalued analysis, general Lyapunov method, topolog...

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