A transition entropy area estimation method for combinational circuits

A new area estimation model with transition information entropy has been proposed by considering the behavioral relationship and similarity between input and output signals of logic circuits. The probability methods are used to evaluate the similarity and relationship degree between inputs and outputs of circuits. The area estimation algorithm with transition entropy was implemented on a lot of random circuits and BENCHMARK circuits, and the experimental results show 3% better estimation precision at least for logic circuits with m-input and one-output.