...
首页> 外文期刊>Mathematical Problems in Engineering >Fixed Points and Exponential Stability for Impulsive Time-Delays BAM Neural Networks via LMI Approach and Contraction Mapping Principle
【24h】

Fixed Points and Exponential Stability for Impulsive Time-Delays BAM Neural Networks via LMI Approach and Contraction Mapping Principle

机译:基于LMI方法和压缩映射原理的脉冲时滞BAM神经网络的不动点和指数稳定性

获取原文
获取原文并翻译 | 示例
           

摘要

The fixed point technique has been employed in the stability analysis of time-delays bidirectional associative memory (BAM) neural networks with impulse. By formulating a contraction mapping in a product space, a new LMI-based exponential stability criterion was derived. Lately, fixed point methods have educed various good results inspiring this work, but those criteria cannot be programmed by a computer. In this paper, LMI conditions of the obtained result can be applicable to computer Matlab LMI toolbox which meets the need of the large-scale calculation in real engineering. Moreover, a numerical example and a comparable table are presented to illustrate the effectiveness of the proposed methods.
机译:不固定点技术已被用于具有脉冲的时滞双向联想记忆(BAM)神经网络的稳定性分析中。通过在产品空间中制定收缩映射,得出了一个新的基于LMI的指数稳定性准则。最近,定点方法产生了各种良好的结果,启发了这项工作,但是这些标准无法由计算机进行编程。本文所获得的结果的LMI条件可以应用于计算机Matlab LMI工具箱,满足实际工程中大规模计算的需要。此外,给出了一个数值示例和一个可比较的表格来说明所提出方法的有效性。

著录项

  • 来源
    《Mathematical Problems in Engineering》 |2016年第10期|3154683.1-3154683.8|共8页
  • 作者单位

    Chengdu Normal Univ, Dept Math, Chengdu 611130, Sichuan, Peoples R China;

    Chengdu Normal Univ, Dept Math, Chengdu 611130, Sichuan, Peoples R China|Chengdu Normal Univ, Inst Math, Chengdu 611130, Sichuan, Peoples R China;

    Chengdu Normal Univ, Dept Math, Chengdu 611130, Sichuan, Peoples R China|Chengdu Normal Univ, Inst Math Educ, Chengdu 611130, Sichuan, Peoples R China;

    Chengdu Normal Univ, Dept Math, Chengdu 611130, Sichuan, Peoples R China|Chengdu Normal Univ, Inst Math Educ, Chengdu 611130, Sichuan, Peoples R China;

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

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