Existence and stability of periodic solutions for Hopfield neural network equations with periodic input

被引:60
作者
Dong, QX [1 ]
Matsui, K
Huang, XK
机构
[1] Tokyo Denki Univ, Coll Sci & Engn, Hatoyama, Saitama 3500394, Japan
[2] Beijing Inst Business, Math Sect, Beijing 100081, Peoples R China
关键词
Hopfield neural network; continuation theorem; periodic solution; existence and stability;
D O I
10.1016/S0362-546X(01)00113-4
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The existence and stability of periodic solutions for the general Hopfield neural network equations with periodic input and delay argument were studied. An operator equation was used to obtain a periodic solution in Banach space. The uniqueness of the periodic solution was also studied.
引用
收藏
页码:471 / 479
页数:9
相关论文
共 3 条
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Gaines R. E., 1977, Coincidence degree, and nonlinear differential equations
[2]   NEURONS WITH GRADED RESPONSE HAVE COLLECTIVE COMPUTATIONAL PROPERTIES LIKE THOSE OF 2-STATE NEURONS [J].
HOPFIELD, JJ .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES, 1984, 81 (10) :3088-3092
[3]  
李铁成, 1997, [高校应用数学学报. A辑, Applied Mathematics: A Journal of Chinese Universities], V12, P25