数学理论与应用 ›› 2016, Vol. 36 ›› Issue (3): 25-36.

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噪声抑制Cohen-Grossberg神经网络模型的指数增长

王娟君, 林巧, 苏辉   

  1. 长沙理工大学数学与统计学院,长沙,410004
  • 出版日期:2016-09-30 发布日期:2020-09-27

Noise Supress Exponential Growth for Cohen-Grossberg Neural Networks

Juanjun Wang, Qiao Lin, Hui Su   

  1. School of Mathematics and Statistics,Changsha University of Science and Technology,Changsha 410004,China

  • Online:2016-09-30 Published:2020-09-27

摘要: 本文研究了噪声对Cohen-Grossberg神经网络模型的影响,当Cohen-Grossberg神经网络模型的解为指数增长时,若加入适当的噪声可以使得相对应的随机Cohen-Grossberg神经网络模型的解为多项式增长,即噪声可以抑制Cohen-Grossberg神经网络模型的指数增长.

关键词: 指数增长, 多项式增长, 马氏链, Cohen-Grossberg神经网络

Abstract: In this letter,we will show that noise can make a given Cohen-Grossberg neural networks whose solution may grows exponentially become the new stochastic Cohen-Grossberg neural networks whose solution will grow at most polynomially.In other words,we reveal that the noise can suppress the exponential growth for Cohen-Grossberg neural networks.

Key words: Exponential growth, Polynomial growth, Markov chain, Cohen-Grossberg neural networks