Abstract
Similarity testing for circuits is an important task in the identification of possible infringement of intellectual property rights. In this paper, we propose a novel procedure for global similarity measurement between circuit topologies (networks) and apply this procedure to the comparison of physical designs of circuits. We first construct networks to describe the way in which circuit elements interact. Then, we evaluate the properties of each node from the resulting networks by calculating the cumulative distribution of characteristic parameters such as degree, clustering coefficient, etc. Based on the maximum vertical distance of each pair of distributions, global similarity testing methods are proposed with consideration of the inhomogeneity of parameter distributions and the scale of the networks. Simulation results show the effectiveness of the strategy in terms of robustness and topological information mining. The methodology described here can be applied to the identification of physical designs of circuits that may contain suspected patent infringement, and it is suitable for a wide range of circuits and systems.
Original language | English |
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Pages (from-to) | 96-103 |
Number of pages | 8 |
Journal | Applied Mathematics and Computation |
Volume | 230 |
DOIs | |
Publication status | Published - 1 Mar 2014 |
Keywords
- Circuits
- Complex networks
- Cumulative distribution
- Global similarity tests
- Physical design
ASJC Scopus subject areas
- Applied Mathematics
- Computational Mathematics