IBMG: Interpretable Behavioral Model Generator for Nonlinear Analog Circuits via Canonical Form Functions and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{McConaghy_2005_iscas,
  author =       "Trent McConaghy and Georges Gielen",
  title =        "IBMG: Interpretable Behavioral Model Generator for
                 Nonlinear Analog Circuits via Canonical Form Functions
                 and Genetic Programming",
  booktitle =    "Proceedings of the IEEE International Symposium on
                 Circuits and Systems (ISCAS)",
  year =         "2005",
  pages =        "5170--5173",
  month =        "23-26 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  broken =       "http://www.epapers.org/iscas2005/ESR/paper_details.php?paper_id=5387",
  DOI =          "doi:10.1109/ISCAS.2005.1465799",
  URL =          "http://trent.st/content/2005-ISCAS-ibmg.pdf",
  size =         "4 pages",
  abstract =     "This paper presents IBMG, an approach to generate
                 behavioral models of nonlinear analog circuits, with
                 the special distinction that it generates models that
                 are compact, interpretable expressions, which are not
                 restricted to any pre-defined functional templates.
                 IBMG outputs a small set of interpretable nonlinear
                 differential equations that approximate the time-domain
                 behavior of the circuit being modeled. The approach
                 uses genetic programming (GP), which evolves functions,
                 but GP has been heavily modified so that the behavioral
                 expressions follow a special canonical functional form
                 grammar to remain interpretable. IBMG has explicit
                 error control: it provides a set of models that trade
                 off complexity and accuracy. Experimental results on a
                 strongly nonlinear latch circuit demonstrate the
                 usefulness of IBMG.",
}

Genetic Programming entries for Trent McConaghy Georges G E Gielen

Citations