Crosstalk Prediction in Non-uniform Cable Bundles Based on Neural Network

摘要：

The statistical approaches for estimating crosstalk in random cable bundles require significant computational effort. The “worst-case method can mitigate overmuch computation, but it gives a too conservative prediction. In order to account for these problems, a neural network approach to predict crosstalk in non-uniform cable bundles at low frequencies where circuits are electrically small is proposed. A BP neural network model is trained by Levenberg-Marquardt algorithm based on statistical simulation results calculated by RDSI algorithm. By comparing the predicted results and the simulation ones, an adequate match between them shows that the proposed neural network method has the ability to predict crosstalk in non-uniform cable bundles rapidly and accurately.

作者: Fei Dai Guihao Bao DongLin Su

作者单位: School of Electronics and Information engineering, Beihang University EMC Lab, Beijing, 100191, Chin School of Electronics and Information engineering, Beihang UniversityEMC Lab, Beijing, 100191, China

会议类型: 国际会议

会议名称: 第九届国际天线、电波传播及电磁理论学术研讨会(ISAPE2010)

会议地点: 广州

会议语种:英文

页码: 1-4

在线出版日期: 2010-11-29（万方平台首次上网日期，不代表论文的发表时间）