Ant colony optimization algorithm for design of analog filters

Abstract

Filters are important building blocks in signal processing circuits. Some researcher had successfully utilized genetic algorithm (GA) in design of filters. Nevertheless, filters obtained by GA are always complex and require lengthy computations. Ant colony optimization (ACO) is a novel searching technique used in optimization problems. In this paper, an ACO approach for optimization of analog filters is presented. In a design example, the order of a lowpass filter and the parameters of its components have been optimized in a discrete search space. AC analysis of the optimized filter has been conducted, and the results have been compared with a filter obtained by GA. The results show that filters obtained by ACO have simpler structures and better performance.