Automatic design of analog electronic circuits using grammatical evolution

Abstract

A new approach for automatic synthesis of analog electronic circuits based on grammatical evolution is presented. Grammatical evolution is an evolutionary algorithm based on grammar which can generate code in any programming language and uses variable length linear binary strings. The decoding of each chromosome determines which production rules in a Backus-Naur Form grammar definition are used in a genotype-to-phenotype mapping process. In our method, decoding focuses on obtaining circuit netlists. A new grammar for generating such netlists and a variant of the XOSites-based crossover operator are also presented. A post-processing stage is needed to adapt the decoded netlist prior its evaluation using the NGSpice simulator. Our approach was applied to several case studies, comprising a total of seven benchmark circuits. A comparison with previous works in the literature shows that our method produces competitive circuits in relation to the degree of compliance with the output specifications, the number of components and the number of evaluations used in the evolutionary process.