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A NEURAL-BASED NONLINEAR L1-NORM OPTIMIZATION ALGORITHM FOR DIAGNOSIS OF NETWORKS*
  • ISSN号:0217-9822
  • 期刊名称:《电子科学学刊:英文版》
  • 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]
  • 相关基金:Supported by Doctoral Special Fund of State Education Commission;the National Natural Science Foundation of China,Grant No.59477001 and No.59707002
中文摘要:

Based on exact penalty function, a new neural network for solving the L1-norm optimization problem is proposed. In comparison with Kennedy and Chua’s network(1988), it has better properties.Based on Bandler’s fault location method(1982), a new nonlinearly constrained L1-norm problem is developed. It can be solved with less computing time through only one optimization processing. The proposed neural network can be used to solve the analog diagnosis L1 problem. The validity of the proposed neural networks and the fault location L1 method are illustrated by extensive computer simulations.

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期刊信息
  • 《电子科学学刊:英文版》
  • 主管单位:中国科学院
  • 主办单位:中国科学院电子学研究所
  • 主编:朱敏慧
  • 地址:北京2702信箱
  • 邮编:100080
  • 邮箱:jc@mail.ie.ac.cn
  • 电话:010-62551772
  • 国际标准刊号:ISSN:0217-9822
  • 国内统一刊号:ISSN:11-2003/TN
  • 邮发代号:
  • 获奖情况:
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,荷兰文摘与引文数据库,英国科学文摘数据库
  • 被引量:73