A neural network approach to predict the crosstalk in non-uniform multiconductor transmission lines

A neural network approach is proposed for the prediction of crosstalk in non-uniform multiconductor transmission lines. The non-uniform multiconductor transmission lines is approximated as a cascade of uniform sections and the neural network is suitably trained with few cross section configurations to learn the behavior of the per unit length parameters. The procedure allows a fast and accurate prediction tool to analyze crosstalk in non-uniform multiconductor transmission lines.