Journal of Electroceramics

, Volume 24, Issue 4, pp 245–260 | Cite as

Analyzing results of impedance spectroscopy using novel evolutionary programming techniques

  • A. B. Tesler
  • D. R. Lewin
  • S. Baltianski
  • Y. Tsur


This paper discusses the application of evolutionary programming methods to the problem of analyzing impedance spectroscopy results. The basic approach is a “direct-problem” one, i.e., to find a time constant distribution function that would create similar impedance results as the measured ones, within experimental error. Two complementary methods have been applied and are discussed here: Genetic Algorithm (GA) and Genetic Programming (GP). A GA can be applied when a known (or desired) model exists, whereas GP can be used to create new models where the only a-priori knowledge is their smoothness and their non-negativity. GP is tuned to prefer relatively non-complex models through penalization of unnecessary complexity.


Impedance spectroscopy Evolutionary programming Genetic algorithm Genetic programming 



Partial funding of the Technion's Fund for Promotion of Research and the I. Goldberg Fund for Electronic Research are gratefully acknowledged. S.B. would like to acknowledge the support of The Center for Absorption in Science, Israeli Ministry of Immigrant Adsorption. We would also like to thank an anonymous reviewer for very thorough reading of the manuscript and useful suggestions.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • A. B. Tesler
    • 1
  • D. R. Lewin
    • 1
  • S. Baltianski
    • 1
  • Y. Tsur
    • 1
  1. 1.Department of Chemical EngineeringTechnion, IITHaifaIsrael

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