Application of the univariate marginal distribution algorithm to analog circuit design

The approach to computer aided analog circuit design on the base of univariate algorithms was derived by the analysing the mathematical principles behind recombination. A Bayesian prior using for the estimations of the probability distribution is equivalent to having mutation for the genetic algorithms. In this paper the relation between a success rate and a mutation one is considered for analog circuit design. Practical illustration of the use of this approach is demonstrated for filter design. Experiments indicate that mutation and elitism increase the performance of the algorithms and decrease the dependence of the correct choice of the population size.