Application of the Univariate Marginal Distribution Algorithm to Analog Circuit Design

Authors:
Lyudmilla Zinchenko;Heinz Mühlenbein;Victor Kureichik;Thilo Mahnig
Affiliations:
-;-;-;-
Venue:
EH '02 Proceedings of the 2002 NASA/DoD Conference on Evolvable Hardware (EH'02)
Year:
2002

Citing 0
Cited 3

Effective mutation rate for probabilistic evolutionary design of analogue electrical circuits

Applied Soft Computing
Multi-objective univariate marginal distribution optimisation of mixed analogue-digital signal circuits

Proceedings of the 9th annual conference on Genetic and evolutionary computation
A comparison of different circuit representations for evolutionary analog circuit design

ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware

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Abstract

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 isconsidered for analog circuit design. Practical illustration of the use of this approach is demonstrated for filter design. Experiments indicate that mutation and elitism increase theperformance of the algorithms and decrease the dependence of the correct choice of the population size.