A hypercube minimization algorithm for Boolean functions

The hypercube concepts, properties, and architecture are used to represent and minimize Boolean functions. The hypercube representation of Boolean functions lends itself directly to parallel implementation of the minimization technique developed in this paper. A new hypercube property, called Telescopic Property is established to allow the representation of a function having a large number of variables on a small dimensional hypercube. A parallel algirithm is suggested lo combine the prime implicants into essential prime implicants in a systematic way. The parallel algorithm can be implemented on a hypercube machine of any size.