计算物理 ›› 2009, Vol. 26 ›› Issue (2): 311-316.

• 研究论文 • 上一篇    

互连导线串扰问题的人工神经网络预测

李旭, 俞集辉, 李永明, 汪泉弟   

  1. 重庆大学输配电装备及系统安全与新技术国家重点实验室, 重庆 400030
  • 收稿日期:2007-07-09 修回日期:2008-03-23 出版日期:2009-03-25 发布日期:2009-03-25
  • 作者简介:李旭(1978-),男,四川西昌市,博士,从事电磁兼容方面的研究,重庆长安汽车工程研究院电装设计所401120.
  • 基金资助:
    重庆市自然科学基金重点(CSTC,2006BA6015)资助项目

Artificial Neural Network Prediction of Crosstalk Coupling Between Interconnecting Wires

LI Xu, YU Jihui, LI Yongming, WANG Quandi   

  1. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400030, China
  • Received:2007-07-09 Revised:2008-03-23 Online:2009-03-25 Published:2009-03-25

摘要: 提出应用人工神经网络对互连导线间串扰问题进行预测的方法.选择对互连导线串扰响应有影响的相关参数作为输入预测因子,用基于误差反向传播的BP网络构造输入预测因子与串扰响应输出之间的映射关系,并用MTL和FDTD法计算获得的训练样本集对构造好的BP网络进行训练,建立基于BP网络的导线串扰的预测模型.最后,将串扰的BP预测结果和和测试样本进行比较,表明该方法有效.

关键词: 互连导线, 串扰, 电磁兼容, 人工神经网络, 预测

Abstract: A method predicting crosstalk coupling between interconnecting wires with artificial neural networks is proposed.Parameters that influence crosstalk coupling are selected as input prediction factors.Back propagation neural network constructs a mapping relation between input prediction factors and output crosstalk coupling of interconnecting wires.Learning sample sets computed by MTL and FDTD method are used to train BP networks.A prediction BP model is obtained.BP predictions and test sample results are compared.

Key words: interconnecting wires, crosstalk coupling, electromagnetic compatibility, artificial neural networks, prediction

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