A neural network approach to PLA folding problems

A near-optimum parallel algorithm for solving PLA folding problems is presented in this paper where the problem is NP-complete and one of the most fundamental problems in VLSI design. The proposed system is composed of n/spl times/n neurons based on an artificial two-dimensional maximum neural network where n is the number of inputs and outputs or the number of product lines of PLA. The two-dimensional maximum neurons generate the permutation of inputs and outputs or product lines. Our algorithm can solve not only a simple folding problem but also multiple, bipartite, and constrained folding problems. We have discovered improved solutions in four benchmark problems over the best existing algorithms using the proposed algorithm.