Representations of Logic Functions Using QRMDDs

This paper considers quasi-reduced multi-valued decision diagrams with bits (QRMDD( )s) to represent twovalued logic functions. It shows relations between the numbers of nodes in QRMDD( )s and values of for benchmark functions; an upper bound on the number of nodes in the QRMDD( ); difference between the upper bound and the number of nodes in the QRMDD( )s for random functions; and the amount of total memory, evaluation time, and areatime complexity for QRMDD( )s. Experimental results using standard benchmark functions show that the area-time complexity takes its minimum when is between ¿and .

• Type: Conference
• Year: 2002
• Where: ISMVL
• Authors: Shinobu Nagayama, Tsutomu Sasao, Yukihiro Iguchi, Munehiro Matsuura
• Keywords: Artificial Intelligence, Benchmark Functions, ISMVL 2002, Multi-valued Decision Diagrams, Upper Bound