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A neural network approach to PLA folding problems

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

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

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