人工神经网络
算法
基质(化学分析)
时域有限差分法
计算机科学
串扰
电子工程
拓扑(电路)
物理
工程类
材料科学
电气工程
人工智能
光学
复合材料
作者
Chengpan Yang,Wei Yan,Yang Zhao,Yang Chen,Chongming Zhu,Zhibo Zhu
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2019-01-01
卷期号:7: 126315-126322
被引量:18
标识
DOI:10.1109/access.2019.2935467
摘要
A new method based on back propagation (BP) neural network for extracting RLCG parameter matrix of multi-core twisted cable is presented.With the properly selected parameter matrix sample, the variation characteristics of the parameter matrix of the multi-core twisted cable can be learned by the Levenberg-Marquardt (L-M) algorithm based on BP neural network.The proposed method is combined with the finite-difference time-domain (FDTD) method to calculate the near end crosstalk (NEXT) and the far end crosstalk (FEXT) of the multi-core twisted cable.To verify the new method, a three-core twisted cable is measured and analyzed in the frequency band of 100 kHz -1 GHz.The results show that the verification error of the extraction network of the RLCG parameter matrix has good accuracy, which does not exceed 0.8%.Compared with the full wave method, the maximum deviations of FEXT and NEXT solved by the proposed methods are -2.71dB and 10.56 dB, respectively, which are better than 29.32 dB and 32.45 dB solved by the conventional method.
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