Applied Mathematics and Mechanics (English Edition) ›› 2002, Vol. 23 ›› Issue (12): 1367-1373.

• 论文 • 上一篇    下一篇

ON THE ASYMPTOTIC BEHAVIOR OF HOPFIELD NEURAL NETWORK WITH PERIODIC INPUTS

向兰1, 周进1,2, 刘曾荣2, 孙姝3   

  1. 1. Department of Physics, Hebei University of Technology, Tianjin 300130, P. R. China;
    2. Department of Mathematics, Shanghai University, Shanghai 200436, P. R. China;
    3. Naval Submarine Academy, Qingdao 266071, P. R. China
  • 收稿日期:2001-07-24 修回日期:2002-04-30 出版日期:2002-12-18 发布日期:2002-12-18

ON THE ASYMPTOTIC BEHAVIOR OF HOPFIELD NEURAL NETWORK WITH PERIODIC INPUTS

XIANG Lan1, ZHOU Jin1,2, LIU Zeng-rong2, SUN Shu3   

  1. 1. Department of Physics, Hebei University of Technology, Tianjin 300130, P. R. China;
    2. Department of Mathematics, Shanghai University, Shanghai 200436, P. R. China;
    3. Naval Submarine Academy, Qingdao 266071, P. R. China
  • Received:2001-07-24 Revised:2002-04-30 Online:2002-12-18 Published:2002-12-18

摘要: Without assuming the boundedness and differentiability of the nonlinear activation functions,the new sufficient conditions of the existence and the global exponential stability of periodic solutions for Hopfield neural network with periodic inputs are given by using Mawhin’s coincidence degree theory and Liapunov’s function method.

Abstract: Without assuming the boundedness and differentiability of the nonlinear activation functions,the new sufficient conditions of the existence and the global exponential stability of periodic solutions for Hopfield neural network with periodic inputs are given by using Mawhin’s coincidence degree theory and Liapunov’s function method.

中图分类号: 

APS Journals | CSTAM Journals | AMS Journals | EMS Journals | ASME Journals