Information relationships and measures in application to logic design

In this paper, the theory of information relationships and relationship measures is considered and its application to logic design is discussed. This theory makes operational the famous theory of partitions and set systems of Hartmanis. The information relationships and measures enable us to analyze relationships between the modeled information streams and constitute an important analysis apparatus that can be used for analysis and synthesis of various information systems. It can be applied in logic design, pattern analysis, machine learning, and other fields. This paper shows how to apply the relationships and measures to logic design when using as examples three important problems: input support minimization, parallel decomposition and serial functional decomposition. The application examples and experimental results presented in the paper demonstrate the high potential of the information relationships and measures in solving logic synthesis problems.