• 대한수학회논문집
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• 제29권2호
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• pp.227-237
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• 2014

For an $m{\times}n$ nonnegative integral matrix A, a generalized inverse of A is an $n{\times}m$ nonnegative integral matrix G satisfying AGA = A. In this paper, we characterize nonnegative integral matrices having generalized inverses using the structure of nonnegative integral idempotent matrices. We also define a space decomposition of a nonnegative integral matrix, and prove that a nonnegative integral matrix has a generalized inverse if and only if it has a space decomposition. Using this decomposition, we characterize nonnegative integral matrices having reflexive generalized inverses. And we obtain conditions to have various types of generalized inverses.

• Journal of Computing Science and Engineering
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• 제4권2호
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• pp.97-109
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• 2010

Nonnegative matrix factorization (NMF) is a popular method for multivariate analysis of nonnegative data, which is to decompose a data matrix into a product of two factor matrices with all entries restricted to be nonnegative. NMF was shown to be useful in a task of clustering (especially document clustering), but in some cases NMF produces the results inappropriate to the clustering problems. In this paper, we present an algorithm for orthogonal nonnegative matrix factorization, where an orthogonality constraint is imposed on the nonnegative decomposition of a term-document matrix. The result of orthogonal NMF can be clearly interpreted for the clustering problems, and also the performance of clustering is usually better than that of the NMF. We develop multiplicative updates directly from true gradient on Stiefel manifold, whereas existing algorithms consider additive orthogonality constraints. Experiments on several different document data sets show our orthogonal NMF algorithms perform better in a task of clustering, compared to the standard NMF and an existing orthogonal NMF.

• 대한수학회지
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• 제36권4호
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• pp.773-785
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• 1999

Shifts of finite type are represented by nonnegative integral square matrics, and conjugacy between two shifts of finite type is determined by strong shift equivalence between the representing nonnegative intergral square matrices. But determining strong shift equivalence is usually a very difficult problem. we develop splittings and amalgamations of nonnegative integral matrices, which are analogues of those of directed graphs, and show that two nonnegative integral square matrices are strong shift equivalent if and only if one is obtained from a higher matrix of the other matrix by a series of amalgamations.

• Journal of applied mathematics & informatics
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• 제14권1_2호
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• pp.51-67
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• 2004

A matrix pair $(X_0,\;Y_0)$ is called a Hermitian nonnegative-definite(respectively, positive-definite) solution to the matrix equation $GXG^*\;+\;HYH^*\;=\;C$ with unknown X and Y if $X_{0}$ and $Y_{0}$ are Hermitian nonnegative-definite (respectively, positive-definite) and satisfy $GX_0G^*\;+\;HY_0H^*\;=\;C$. Necessary and sufficient conditions for the existence of at least a Hermitian nonnegative-definite (respectively, positive-definite) solution to the matrix equation are investigated. A representation of the general Hermitian nonnegative-definite (respectively positive-definite) solution to the equation is also obtained when it has such solutions. Two presented examples show these advantages of the proposed approach.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권5호
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• pp.347-352
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• 2009

주어진 비음수 데이터를 두 개의 비음수 행렬의 곱의 형태로 표현하는 비음수 행렬 분해(Nonnegative Matrix Factorization)는 비음수 데이터의 다변량 분석에서 폭넓게 사용되고 있는 방법이다. 비음수 행렬 분해는 집단화(Clustering), 특히 문서의 집단화에서 유용하게 쓰일 수 있다. 본 논문에서는 주어진 문서들로부터 구성된 단어-문서 행렬을 두 개의 비음수 행렬의 곱으로 분해할 때, 그 중 하나의 행렬에 직교 제한을 주는 비음수 행렬의 직교 분해(Orthogonal Nonnegative Matrix Factorization) 방법을 다룬다. 현존하는 비음수 행렬의 직교 분해 방법은 직교 제한과 관련된 항을 더해주는 방식을 사용하지만, 여기서는 Stiefel 다양체 위에서의 실제 기울기를 직접 구하여 곱셈의 업데이트 알고리즘을 유도하였다. 다양한 문서 데이터에 대한 실험을 통해 새롭게 유도된 비음수 행렬의 직교 분해 방법이 기존의 비음수 행렬 분해나 기존의 비음수 행렬의 직교 분해보다 문서 집단화에서 우수한 성능을 나타냄을 보였다.

• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.169-181
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• 2007

Applying the properties of Hadamard core for totally nonnegative matrices, we give new lower bounds of the determinant for Hadamard product about matrices in Hadamard core and totally nonnegative matrices, the results improve Oppenheim inequality for tridiagonal oscillating matrices obtained by T. L. Markham.

• Journal of applied mathematics & informatics
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• 제23권1_2호
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• pp.337-344
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• 2007

In this paper, we obtain some new bounds for Perron root of a nonnegative matrix, which are expressed by easily calculated function in element of matrix. These new results generalize and improve the bounds of G. Frobenius [1] and H. Minc [2], and also extend the known results by Liu [6].

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제14권3호
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• pp.296-300
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• 2008

최근에 개발된 Nonnegative tensor factorization(NTF)는 비음수 행렬 분해(NMF)의 multiway(multilinear) 확장형이다. NTF는 CANDECOMP/PARAFAC 모델에 비음수 제약을 가한 모델이다. 본 논문에서는 Tucker 모델에 비음수 제약을 가한 nonnegative Tucker decomposition(NTD)라는 새로운 텐서 분해 모델을 제안한다. 제안된 NTD 모델을 least squares, I-divergence, $\alpha$-divergence를 이용한 여러 목적함수에 대하여 fitting하는 multiplicative update rule을 유도하였다.

• Kyungpook Mathematical Journal
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• 제53권2호
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• pp.273-283
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• 2013

In this paper, we consider the row rank inequalities derived from comparisons of the row ranks of the additions and multiplications of nonnegative integer matrices and construct the sets of nonnegative integer matrix pairs which is occurred at the extreme cases for the row rank inequalities. We characterize the linear operators that preserve these extreme sets of nonnegative integer matrix pairs.

• 한국전자통신학회논문지
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• 제6권2호
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• pp.193-198
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• 2011

행렬들 중 그것의 성분으로 부호인 + 와 0 만을 갖는 행렬을 우리는 비음인 부호화 행렬이라 한다. 또한 비음인 부호화 행렬 A가 그것과 같은 부호를 갖는 실수 정규행렬 B가 존재하면 정규성을 허용한다고 한다. 본 논문은 참고문헌[1] 에서 밝힌 형태와 다른 특별한 형태를 조사했고, 실수 행렬 중 비음인 정규행렬을 구성하는 흥미로운 방법을 제공했다.