A hybrid integral equation and neural network approach for fast extraction of frequency dependent parameters of multiconductor transmission lines

Multiconductor transmission lines (MTL) have been modeled by the distributed parameters R, L, C, and G in many commercial CAD packages, where most of the parameters are assumed to be frequency independent or at most R ∝ √f. At gigahertz frequencies, such assumptions may introduce significantly large errors in the waveform simulation and timing. In this article, we present a new and fast technique based on a combination of neural network techniques and the integral equation method (IEM) to evaluate frequency dependences accurately, while dramatically reducing the computation time.