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一类有限分布延时的神经网络的全局耗散性
  • ISSN号：1671-6841
  • 期刊名称：《郑州大学学报：理学版》
  • 时间：0
  • 分类：O175.1[理学—数学;理学—基础数学]
  • 作者机构：[1]燕山大学数学物理系,河北秦皇岛066004
  • 相关基金：国家自然科学基金资助（10571035）.
作者： 武怀勤[1], 孙建枝[1]
关键词： 神经网络, 全局耗散性, 分布延时, neural networks, global dissipativity, distributed delays
中文摘要：

通过构造径向无界的正定的Lyapunovh函数，研究一类具有有限分布延时的神经网络的全局耗散性，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此条件的有效性．

英文摘要：

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

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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