• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.109-117
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• 2014

This paper revises the Quine-McCluskey Algorithm to circuit minimization problems. Quine-McCluskey method repeatedly finds the prime implicant and employs additional procedures such as trial-and-error, branch-and-bound, and Petrick's method as a means of circuit minimization. The proposed algorithm, on the contrary, produces an implicant chart beforehand to simplify the search for the prime implicant. In addition, it determines a set cover to streamline the search for $1^{st}$ and $2^{nd}$ essential prime implicants. When applied to 3-variable and 4-variable experimental data, the proposed algorithm has indeed proved to obtain the optimal solutions much more simply and accurately than the Quine-McCluskey method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.12
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• pp.1288-1295
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• 1990

In this paper, we propose a parallel processing model for the efficient selection of Prime Implicants of Logic Functions. This model consists of simple parallel processing nodes, connections between them, Max Net (a part of Hamming Net) and quasi essential Prime Implicant selection standard in simplified cost form. Through these, this model selects essential Prime Implicants in a certain period of time regardless of the number of given Prime Implicants and minterms and also selects quasi essential Prime Implicants in short time.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.95-102
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• 2015

This paper proposes a simple algorithm for circuit minimization. There are currently two effective heuristics for circuit minimization, namely manual Karnaugh maps and computable Quine-McCluskey algorithm. The latter, however, has a major defect: the runtime and memory required grow $3^n/n$ times for every increase in the number of variables n. The proposed algorithm, however, extracts the prime implicants (PI) that cover minterms of a given Boolean function by deriving an implicants table based on frequency. From a set of the extracted prime implicants, the algorithm then eliminates redundant PIs again based on frequency. The proposed algorithm is therefore capable of minimizing circuits polynomial time when faced with an increase in n. When applied to various 3-variable and 4-variable cases, it has proved to swiftly and accurately obtain the optimal solutions.