GA optimization of terminal antennas by the estimation of the population density of probability using dependency trees

An application to antenna optimization of bayesian network density of probability estimators is presented. This technique is very usefull for optimizations where abig number of parameters, multiple solutions and local minima increase the likelihood to converge towards suboptimale solutions. Three methodes are presented and compared in the case of antenna optimization