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具有有限分布延时的一类神经网络的全局指数耗散性
  • ISSN号：1671-6841
  • 期刊名称：《郑州大学学报：理学版》
  • 时间：0
  • 分类：TP183[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程] O233[理学—运筹学与控制论;理学—数学]
  • 作者机构：[1]燕山大学理学院,河北秦皇岛066004
  • 相关基金：国家自然科学基金资助项目,编号10571035.
作者： 孙虹霞[1], 孙建枝[1], 武怀勤[1]
关键词： 神经网络, 全局指数耗散性, 分布延时, neural network, global exponential dissipativity, distributed delay
中文摘要：

通过构造径向无界正定的Lyapunov函数，研究了一类具有有限分布延时的神经网络的全局指数耗散性，在假定延时可微的情况下，给出了几个确保网络全局耗散性的充分条件．最后通过一个数值例子说明条件的有效性．

英文摘要：

The global exponential dissipativity of a class of neural networks with finite distributed delays is investigated by constructing radically unbounded and positive definite Lyapunov function. Several sufficient conditions are given to guarantee global exponential dissipativity of the neural networks with assuming the differentiability of delay. At last, an example is given to illustrate the applicability of the conditions.

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期刊信息
  • 《郑州大学学报：理学版》
  • 中国科技核心期刊
  • 主管单位:河南省教育厅
  • 主办单位:郑州大学
  • 主编：李燕燕
  • 地址：郑州市高新区科学大道100号
  • 邮编：450001
  • 邮箱：lixueban@zzu.edu.cn
  • 电话：0371-67781272
  • 国际标准刊号：ISSN：1671-6841
  • 国内统一刊号：ISSN：41-1338/N
  • 邮发代号:36-191
  • 获奖情况:
  • 国内外数据库收录:
  • 美国化学文摘（网络版）,美国数学评论（网络版）,波兰哥白尼索引,德国数学文摘,中国中国科技核心期刊,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）,英国英国皇家化学学会文摘
  • 被引量:2791