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A neural network approach to PLA folding problems

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2 Author(s)
K. Tsuchiya ; Fac. of Environ. Inf., Keio Univ., Fujisawa, Japan ; Y. Takefuji

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×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

Published in:

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  (Volume:15 ,  Issue: 10 )