Multiple output minimization

摘要

This paper describes two logic minimization algorithms. CAMP (Computer Aided Minimization Procedure) minimizes single functions. The minterms are covered either by essential prime implicants or by selective prime implicants. The two types of prime implicants are determined one at a time thus completely avoiding the computationally expensive covering problem. The adjacency of a minterm, that depends upon the proximity of this minterm with respect to other minterms on the Karnaugh map, guides the determination of prime implicants. This procedure is nonheuristic and has proved to be very efficient for large number of input variables. The multiple output minimization (MOM) algorithm generates the product terms with maximum sharing between the output functions. In addition to using adjacency, this procedure is also guided by the frequency with which a minterm is used by the functions. Examples show the performance of this algorithm to be equal or better than many other minimization procedures.