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 #