Analog circuit topological feature extraction with unsupervised learning of new sub-structures

Abstract

This paper presents novel techniques to automatically extract the topological (structural) features in analog circuits. The extracted features include basic building blocks, structural templates and hierarchical structures. Finding structural features is important for tasks like circuit synthesis and sizing, design verification, design reuse, and design knowledge description, summarization and management. The paper presents algorithms for supervised feature extraction and unsupervised learning of new block connections. Experiments discuss feature extraction for a set of 34 state-of-the-art analog circuits.