Genetic optimization of interval arithmetic-based worst case circuit tolerance analysis

A new approach for improving the efficiency and accuracy of interval arithmetic (IA) based worst case (WC) circuit tolerance analysis (TA) is presented in this paper. The partitioning of the parameters' tolerance/uncertainty ranges, which is necessary to increase the accuracy of IA-based computations, is optimized by means of a genetic algorithm (GA). It is shown that the IA-GA approach permits us to solve problems of small-change (SC) as well as large-change (LC) WC circuit TA, accurately and reliably. Several applications to the analysis of circuits with uncertain parameters are presented and discussed.