Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming

  • John R. Koza
  • Forrest H. BennettIII
  • David Andre
  • Martin A. Keane

Abstract

This paper describes an automated process for designing analog electrical circuits based on the principles of natural selection, sexual recombination, and developmental biology. The design process starts with the random creation of a large population of program trees composed of circuit-constructing functions. Each program tree specifies the steps by which a fully developed circuit is to be progressively developed from a common embryonic circuit appropriate for the type of circuit that the user wishes to design. The fitness measure is a user-written computer program that may incorporate any calculable characteristic or combination of characteristics of the circuit. The population of program trees is genetically bred over a series of many generations using genetic programming. Genetic programming is driven by a fitness measure and employs genetic operations such as Darwinian reproduction, sexual recombination (crossover), and occasional mutation to create offspring. This automated evolutionary process produces both the topology of the circuit and the numerical values for each component. This paper describes how genetic programming can evolve the circuit for a difficult-to-design low-pass filter.

Keywords

Analog Circuit Fitness Measure Sexual Recombination Fitness Case Analog Integrate Circuit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • John R. Koza
    • 1
  • Forrest H. BennettIII
    • 1
  • David Andre
    • 1
  • Martin A. Keane
    • 2
  1. 1.Department of Computer ScienceStanford UniversityStanfordUSA
  2. 2.Econometrics Inc.ChicagoUSA

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