Comparison of Two Evolvable Systems in the Automated Analog Circuit Synthesis

Aurora Torres Soto, Eunice E. Ponce, María Dolores Torres, Elva Dı́az, Felipe Padilla · 2009

This paper presents the comparison of two different algorithms: a Univariate Marginal Distribution Algorithm for Analog Circuits (UMDA-AC) and a Genetic Algorithm for Analog Circuits (GA-AC). These algorithms are compared in performing the synthesis of topology and sizing of an analog low pass filter. Modeling of circuits is made by means of a linear representation technique with a variable length chromosome. Evaluation of circuits’ functionality is carried out by Simulation Program with Integrated Circuits Emphasis (Spice), since one of the objectives is to keep as low as possible the amount of non Spice-Simulable circuits while keep elements’ values within preferred ones. Experiments show the effectiveness of a set of evolvable mechanisms in both algorithms, and while GA-AC and its three genetic operators are more able to keep low the rate of non Spice-Simulable circuits; UMDA-AC performs less evaluations by means of its estimated distribution

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