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Analysis on RLCG Parameter Matrix Extraction for Multi-Core Twisted Cable Based on Back Propagation Neural Network Algorithm
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DOI：10.1109/ACCESS.2019.2935467.png)
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摘要
En 中文
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 -2.71 dB and 10.56 dB, respectively, which are better than 29.32 dB and 32.45 dB solved by the conventional method.
Keyword:
Multi-core twisted cable
crosstalk
finite-difference time-domain (FDTD) method
neural network
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IF:
3.6
论文数:
9.8W
被引数:
29.4W
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IEEE ACCESSOAAI
IEEE ACCESSIF3.6
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