• 경영과학
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• 제19권2호
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• pp.155-168
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• 2002

In this paper, some efficient implementation techniques for the multifrontal method, which can be used to compute the Cholesky factor of a symmetric positive definite matrix, are presented. In order to use the cache effect in the cache-based computer architecture, a hybrid method for factorizing a frontal matrix is considered. This hybrid method uses the column Cholesky method and the submatrix Cholesky method alternatively. Experiments show that the hybrid method speeds up the performance of the supernodal multifrontal method by 5%～10%, and it is superior to the Cholesky method in some problems with dense columns or large frontal matrices.

• 한국경영과학회지
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• 제28권1호
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• pp.51-61
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• 2003

In the normal equations approach in which the ordering and factorization phases are separated, the factorization in the augmented system approach is computed dynamically. This means that in the augmented system the numerical factorization should be performed to obtain the non-zero structure of Cholesky factor L. This causes much time to set up the non-zero structure of Cholesky factor L. So, we present a method which can separate the ordering and numerical factorization in the augmented system. Experimental results show that the proposed method reduces the time for obtaining the non-zero structure of Cholesky factor L.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.587-592
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• 2016

It is a long-standing issue to correctly determine the number of long-run relationships among time series processes. We revisit nonparametric test for cointegration rank and propose bootstrap refinements. Consistent with model-free nature of the tests, we make use of Cholesky factor bootstrap methods, which require weak conditions for data generating processes. Simulation studies show that the original Breitung's test have difficulty in obtaining the correct size due to dependence in cointegrated errors. Our proposed bootstrapped tests considerably mitigate size distortions and represent a complementary approach to other bootstrap refinements, including sieve methods.

• The Journal of the Acoustical Society of Korea
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• 제12권2E호
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• pp.47-62
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• 1993

SMI 방법은 수치적인 불안정성과 아울러 많은 계산량을 갖는다. 본 논문에서는 역 공분산 행렬의 Cholesky 분할을 이용하여 SMI 방법보다 효율적인 방법을 제안한다. 제안한 방법에서는 적응 빔 형상과 검출이 하나의 구조로 실현되며 이에 피룡한 역 공분산 행렬의 Cholesky factor는 secondary 입력으로부터 GS 프로세서를 이용하여 추정한다. 제안한 구조의 중요한 특징은 공분산 행렬과 Cholesky factor를 직접 구할 필요가 없다는 점이며, 또한 GS 프로세서의 장점을 이용한 systolic 구조를 사용함으로써 효율적인 계산을 수행할 수 있다. 모의 실험을 통하여 제안한 방법의 성능과 SMI 방법의 성능을 서로 비교하였다. 또한 nonhomogeneous 환경에서 동작하기 위한 방법이 제시되었으며, 아울러 계산량이 많은 GS 구조의 단점을 극복하기 위해 lattice-GS 구조를 이용하는 방법을 제안하였다.

• 대한산업공학회지
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• 제29권1호
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• pp.78-89
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• 2003

Ordering is performed to reduce the amount of fill-ins of the Cholesky factor of a symmetric positive definite matrix. This paper proposes a new ordering algorithm that reduces the fill-ins of the Cholesky factor iteratively by elimination tree rotations and clique separators. Elimination tree rotations have been used mainly to reorder the rows of the permuted matrix for the efficiency of storage space management or parallel processing, etc. In the proposed algorithm, however, they are repeatedly performed to reduce the fill-ins of the Cholesky factor. In addition, we presents a simple method for finding a minimal node separator between arbitrary two nodes of a chordal graph. The proposed reordering procedure using clique separators enables us to obtain another order of rows of which the number of till-ins decreases strictly.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.289-292
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• 1996

In Cholesky factorization of the interior point method, dense columns of A matrix make dense Cholesky factor L regardless of sparsity of A matrix. We introduce a method to transform a primal problem to a dual problem in order to preserve the sparsity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.810-831
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• 2019

Recently, continuous dimensional emotion recognition from audiovisual clues has attracted increasing attention in both theory and in practice. The large amount of data involved in the recognition processing decreases the efficiency of most bimodal information fusion algorithms. A novel algorithm, namely the incomplete Cholesky decomposition based kernel cross factor analysis (ICDKCFA), is presented and employed for continuous dimensional audiovisual emotion recognition, in this paper. After the ICDKCFA feature transformation, two basic fusion strategies, namely feature-level fusion and decision-level fusion, are explored to combine the transformed visual and audio features for emotion recognition. Finally, extensive experiments are conducted to evaluate the ICDKCFA approach on the AVEC 2016 Multimodal Affect Recognition Sub-Challenge dataset. The experimental results show that the ICDKCFA method has a higher speed than the original kernel cross factor analysis with the comparable performance. Moreover, the ICDKCFA method achieves a better performance than other common information fusion methods, such as the Canonical correlation analysis, kernel canonical correlation analysis and cross-modal factor analysis based fusion methods.

• 한국정보처리학회논문지
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• 제3권2호
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• pp.359-368
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• 1996

본 논문에서는 다행관측행렬 Z$^T$를 빠르게 downdating하기 위하여 Z$^T$의 partial Cholesky factor Rz를 계산하는 전처리 과전을 거친 후, RZ에 각각 기존의 GD(Givens Downdting)기법과 HD(Hyperbolic Downdating)기법을 적용한 PGD(Preprocessed GD)기법 과 PHD(Preprocessed HD)기법을 제안하였다. p$\times$n(p$\geq$n)크기의 다행관측행렬 ZT를 downdating 하는 데필요한 시간복잡도는 PGD 및 PHD기법을 이용한downdating의 경우 에 각각 $pn^2$＋$5n^3/6$ 및 $pn^2$ ＋$n^3/3$ flops이며, 기존의GD기법또는 HD기법을이용한 downdating에서는 각각 5np2/2 과 2np2 flops이므로 다행관측행렬 Z$^T$를 partial Cholesky factor RTZ로 분할하는 전처리 과정이 downdating알고리즘의 성능을 개선할 수 있음을 보여준다. Sun SPARC/2 시스템에서의 벤치 마크 실험 결과도 전처리 과정을 거친 알고리즘의 실행 속도가 전 처리 과정을 거치지 않은 알고리즘에 비하여 빠른 결과 를 얻었으며, 두가지 전처리 기법 중에서도 PHD 기법이 PGD기법 보다 시간복잡도 측면 에서 우수하였다.

• Management Science and Financial Engineering
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• 제8권1호
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• pp.1-19
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• 2002

Ordering is used to reduce the amount of fill-ins in the Cholesky factor of a symmetric positive definite matrix. One of the most efficient ordering methods is the minimum degree ordering algorithm(MDO). In this paper, we provide a few techniques that improve the performance of MDO implemented with the clique storage scheme. First, the absorption of nodes in the cliques is developed which reduces the number of cliques and the amount of storage space required for MDO. Second, we present a modified minimum degree ordering algorithm of which the number of degree updates can be reduced by introducing the lower bounds of degrees. Third, using both the lower and upper bounds of degrees, we develop an approximate minimum degree ordering algorithm. Experimental results show that the proposed algorithm is competitive with the minimum degree ordering algorithm that uses quotient graphs from the points of the ordering time and the nonzeros in the Cholesky factor.

• 대한토목학회논문집
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• 제10권4호
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• pp.95-101
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• 1990

이 논문은 정규방정식을 사용하지 않고서 관측방정식으로부터 직접 직교분해법을 이용하여 측지망을 조정하는 데 목적이 있다. 연구결과, 이 방법은 자유망이나 가중측점조건에 의한 망조정의 경우에 있어서도 효과적으로 안정된 해를 제공하고 정규방정식에서의 Cholesky factor를 활용할 수 있는 등 중규모의 망조정에 적합함을 보여주고 있다.