Boolean functions with long prime implicants

In this short note we introduce a hierarchy of classes of Boolean functions, where each class is defined by the minimum allowed length of prime implicants of the functions in the class. We show that for a given DNF and a given class in the hierarchy, it is possible to test in polynomial time whether the DNF represents a function from the given class. For the first class in the hierarchy we moreover present a polynomial time algorithm which for a given input DNF outputs a shortest logically equivalent DNF, i.e. a shortest DNF representation of the underlying function. This class is therefore a new member of a relatively small family of classes for which the Boolean minimization problem can be solved in polynomial time. For the second class and higher classes in the hierarchy we show that the Boolean minimization problem can be approximated within a constant factor.     

Fast computation of the prime implicants by exact direct-cover algorithm based on the new partial ordering operation rule

In this study, a novel OFF-set based direct-cover Exact Minimization Algorithm (EMA) is proposed for single-output Boolean functions represented in a sum-of-products form. To obtain the complete set of prime implicants covering the given Target Minterm (ON-minterm), the proposed method uses OFF-cubes (OFF-minterms) expanded by this Target Minterm. The amount of temporary results produced by this method does not exceed the size of the OFF-set. In order to achieve the goal of this study, which is to make faster computations, logic operations were used instead of the standard operations. Expansion OFF-cubes, commutative absorption operations and intersection operations are realized by logic operations for fast computation. The proposed minimization method is tested on several classes of benchmarks and then compared with the ESPRESSO algorithm. The results show that the proposed algorithm obtains more accurate and faster results than ESPRESSO does.     

Minimal covering problem and PLA minimization

Solving the minimal covering problem by an implicit enumeration method is discussed. The implicit enumeration method in this paper is a modification of the Quine-McCluskey method tailored to computer processing and also its extension, utilizing some new properties of the minimal covering problem for speedup. A heuristic algorithm is also presented to solve large-scale problems. Its application to the minimization of programmable logic arrays (i.e., PLAs) is shown as an example. Computational experiences are presented to confirm the improvements by the implicit enumeration method discussed.This work was supported in part by the National Science Foundation under Grants Nos. MCS77-09744 and MCS81-08505 and also by the Department of Computer Science.M.-H. Young was with the Department of Computer Science, University of Illinois, Urbana, Illinois.