Extraction of passive device model parameters using genetic algorithms

Ilgu Yun, Lawrence A. Carastro, Ravi Poddar, Martin A. Brooke, Gary S. May, Kyung Sook Hyun, Kwang Eui Pyun

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


The extraction of model parameters for embedded passive components is crucial for designing and characterizing the performance of multichip module (MCM) substrates. In this paper, a method for optimizing the extraction of these parameters using genetic algorithms is presented. The results of this method are compared with optimization using the Levenberg-Marquardt (LM) algorithm used in the HSPICE circuit modeling tool. A set of integrated resistor structures are fabricated, and their scattering parameters are measured for a range of frequencies from 45 MHz to 5 GHz. Optimal equivalent circuit models for these structures are derived from the s-parameter measurements using each algorithm. Predicted s-parameters for the optimized equivalent circuit are then obtained from HSPICE. The difference between the measured and predicted s-parameters in the frequency range of interest is used as a measure of the accuracy of the two optimization algorithms. It is determined that the LM method is extremely dependent upon the initial starting point of the parameter search and is thus prone to become trapped in local minima. This drawback is alleviated and the accuracy of the parameter values obtained is improved using genetic algorithms.

Original languageEnglish
Pages (from-to)38-46
Number of pages9
JournalETRI Journal
Issue number1
Publication statusPublished - 2000 Mar

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Computer Science(all)
  • Electrical and Electronic Engineering


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