Selection of the Optimal Sizes of Analog Integrated Circuits by Fuzzy Sets Intersection

This paper shows the application of Fuzzy sets to select the optimal sizes of analog integrated circuits accomplishing target specifications that are established by linguistic variables, namely: gain “closer to” unity and “large” bandwidth. The cases of study are three unity-gain cells and a current-feedback operational amplifier (CFOA), whose performances characteristics are evaluated by using integrated circuit technology of 0.35μm and 180nm. Every circuit is codified by the width (W) and large (L) of every metal-oxide-semiconductor field-effect-transistor (MOSFET), and by the bias current source, in order to generate a population of feasible solutions by applying the non-dominated sorting genetic algorithm NSGA-II, from which the optimal W and L sizes are selected through the intersection of fuzzy sets. We present the results of the proposed fuzzy selection approach that has been implemented in a sequential and a distributed system, and by applying a zoom technique to search for the optimal sizes in a more detailed or refined way.