首页> 外文期刊>Mathematics and computers in simulation >Noise suppress exponential growth for hybrid Hopfield neural networks
【24h】

Noise suppress exponential growth for hybrid Hopfield neural networks

机译:混合Hopfield神经网络的噪声抑制指数增长

获取原文
获取原文并翻译 | 示例
       

摘要

In this paper, we show that noise can transform a hybrid neural networks, whose solution may grow exponentially, into a new stochastic one, whose solution grows at most polynomially. In other words, we reveal that noise can suppress the exponential growth in hybrid Hopfield neural networks.
机译:在本文中,我们证明了噪声可以将混合神经网络(其解可能呈指数增长)转变为一种新的随机神经网络,其解最多能以多项式增长。换句话说,我们揭示了噪声可以抑制混合Hopfield神经网络中的指数增长。

著录项

  • 来源
    《Mathematics and computers in simulation》 |2012年第12期|10-20|共11页
  • 作者

    Song Zhu; Yi Shen; Guici Chen;

  • 作者单位

    College of Sciences, China University of Mining and Technology, Xuzhou 221116, China Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;

    Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;

    Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China College of Sciences, Wuhan University of Science and Technology, Wuhan 430081, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Exponential growth; Polynomial growth; Generalized Ito formula; Markov chain;

    机译:指数增长;多项式增长广义的伊藤公式;马尔可夫链;
  • 入库时间 2022-08-18 03:29:08

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号