Crosstalk prediction in twisted bundles by a neural approach

A neural network based procedure is proposed for the crosstalk prediction in twisted bundles. The nonuniform bundle 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.