• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.27-33
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• 2006

Boolean matrices are applied to a variety of areas and used successfully in many applications, and there are many researches on boolean matrices. Most researches deal with the multiplication of boolean matrices, but all of them focus on the multiplication of two boolean matrices and very few researches deal with the multiplication between many n$\times$m boolean matrices and all m$\times$k boolean matrices. The paper discusses the existing optimal algorithms for the multiplication of two boolean matrices are not suitable for the multiplication between a n$\times$m boolean matrix and all m$\times$k boolean matrices, establishes a theory that enables the efficient multiplication of a n$\times$m boolean matrix and all m$\times$k boolean matrices, and shows the execution results of a multiplication algorithm designed with this theory.

• Bulletin of the Korean Mathematical Society
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• v.42 no.3
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• pp.501-507
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• 2005

A Boolean matrix with rank 1 is factored as a left factor and a right factor. The perimeter of a rank-1 Boolean matrix is defined as the number of nonzero entries in the left factor and the right factor of the given matrix. We obtain new characterizations of rank preservers, in terms of perimeter, of Boolean matrices.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.475-484
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• 2004

In general, a matrix A is idempotent if $A^2$ = A. The idempotent matrices play an important role in the matrix theory and some properties of the Boolean matrices are examined. Using the upper diagonal completion process, we give the characterization of the Boolean idempotent matrices in modified Frobenius normal form.

• Bulletin of the Korean Mathematical Society
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• v.45 no.2
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• pp.355-363
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• 2008

For a Boolean rank 1 matrix $A=ab^t$, we define the perimeter of A as the number of nonzero entries in both a and b. The perimeter of an $m{\times}n$ Boolean matrix A is the minimum of the perimeters of the rank-1 decompositions of A. In this article we characterize the linear operators that preserve the perimeters of Boolean matrices.

• Journal of the Korean Mathematical Society
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• v.43 no.3
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• pp.539-552
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• 2006

For an $n{\times}n$ Boolean matrix A, A is called nilpotent if $A^m=O$ for some positive integer m. We consider the set of $n{\times}n$ nilpotent Boolean matrices and we characterize linear operators that strongly preserve nilpotent matrices over Boolean algebras.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.1
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• pp.17-27
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• 2000

A factorization is an extremely important part of multi-level logic synthesis. The number of literals in a factored form is a good estimate of the complexity of a logic function. and can be translated directly into the number of transistors required for implementation. Factored forms are described as either algebraic or Boolean, according to the trade-off between run-time and optimization. A Boolean factored form contains fewer number of literals than an algebraic factored form. In this paper, we present a new method for a Boolean factorization. The key idea is to build an extended co-kernel cube matrix using co-kernel/kernel pairs and kernel/kernel pairs together. The extended co-kernel cube matrix makes it possible to yield a Boolean factored form. We also propose a heuristic method for covering of the extended co-kernel cube matrix. Experimental results on various benchmark circuits show the improvements in literal counts over the algebraic factorization based on Brayton's co-kernel cube matrix.

• Bulletin of the Korean Mathematical Society
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• v.50 no.6
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• pp.2001-2011
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• 2013

Cho and Kim [4] have introduced the concept of the competition index of a digraph. Similarly, the competition index of an $n{\times}n$ Boolean matrix A is the smallest positive integer q such that $A^{q+i}(A^T)^{q+i}=A^{q+r+i}(A^T)^{q+r+i}$ for some positive integer r and every nonnegative integer i, where $A^T$ denotes the transpose of A. In this paper, we study the upper bound of the competition index of a Boolean matrix. Using the concept of Boolean rank, we determine the upper bound of the competition index of a nearly reducible Boolean matrix.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.2
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• pp.68-78
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• 2007

D-class is defined as a set of equivalent $n{\times}n$ boolean matrices according to a given equivalence relation. The D-class computation requires the multiplication of three boolean matrices for each of all possible triples of $n{\times}n$ boolean matrices. However, almost all the researches on boolean matrices focused on the efficient multiplication of only two boolean matrices and a few researches have recently been shown to deal with the multiplication of all boolean matrices. The paper suggests a mathematical theory that enables the efficient multiplication for all possible boolean matrix triples and the efficient computation of all D-classes, and discusses algorithms designed with the theory and their execution results.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.197-204
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• 2005

For two distinct rank-1 matrices A and B, a rank-1 matrix C is called a separating matrix of A and B if the rank of A + C is 2 but the rank of B + C is 1 or vice versa. In this case, rank-1 matrices A and B are said to be separable. We show that every pair of distinct Boolean rank-l matrices are separable.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.459-461
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• 2006

The successive multiplication of all $n{\times}n$ boolean matrices is necessary for applications such as D-class computation. But, no research has been performed on it despite many researches dealing with boolean matrices. The paper suggests a theory with which successively multiplying a $n{\times}n$ boolean matrix by all $n{\times}n$ boolean matrices can be done efficiently, applies it to the successive multiplication of all $n{\times}n$ boolean matrices and shows its execution results.