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Global exponential stability of cohen-grossberg neural networks with time-varying delays

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成果类型:
期刊论文
作者:
Wang X.;Li X.;Zhou W.
通讯作者:
Li, X.
作者机构:
[Wang X.; Li X.; Zhou W.] College of Science, Hunan Agricultural University, Changsha, Hunan, 410128, China
通讯机构:
College of Science, Hunan Agricultural University, Changsha, Hunan, China
语种:
英文
关键词:
Time delay;Time varying control systems;Time varying networks;Cohen-Grossberg neural networks;Global exponential stability;M-matrices;Nonlinear measure;Time varying- delays;Neural networks
期刊:
Italian Journal of Pure and Applied Mathematics
ISSN:
1126-8042
年:
2018
期:
40
页码:
126-140
基金类别:
This work was supported by the State’s Key R & D Program of China (Grant No.2017YFD0301507), the Natural Science Foundation of Hunan Province, China (Grant No.2018JJ3227) and Key R & D Program in Hunan Province, China (No.2017NK2382).
机构署名:
本校为第一且通讯机构
院系归属:
理学院
摘要:
In this paper, without the assumptions for boundedness, monotonicity, and differentiability on activation functions and symmetry of interconnections, a class of Cohen-Grossberg neural networks with time-varying delays is studied. A new useful criteria on the uniqueness of equilibrium is obtained by utilizing the nonlinear measure. Combining with Dini derivatives and Young inequality, new sufficient condition for the global exponential stability is established by directly estimating the upper bound of solutions of the system. All results are pre...

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