FUGA: a fuzzy-genetic analog circuit optimization kernel

Abstract

This paper describes an innovative analog circuit design optimization kernel. The new approach generates fuzzy models for qualitative reasoning based on a DOE approach. The models are then used within a standard genetic algorithm implementation enhancing the search by incorporating design knowledge represented by the fuzzy models. The achieved performance is discussed for a set of well known analog circuit structures.