• Communications for Statistical Applications and Methods
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• 제17권6호
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• pp.803-810
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• 2010

The singular value decomposition of a rectangular matrix is a basic tool to understand the structure of the data and particularly the relationship between row and column factors. However, conventional singular value decomposition used the least squares method and is not robust to outliers. We propose a simple robust singular value decomposition algorithm based on the weighted least absolute deviation which is not sensitive to leverage points. Its implementation is easy and the computation time is reasonably low. Numerical results give the data structure and the outlying information.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 추계학술대회
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• pp.47-48
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• 2005

Multidimensional scaling is a multivariate technique for constructing a configuration of n points in Euclidean space using information about the distances between the objects. This can be done by the singular value decomposition of the data matrix. But it is known that the singular value decomposition is not resistant. In this study, we provide a resistant version of the multidimensional scaling.

• 대한수학회지
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• 제50권4호
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• pp.797-811
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• 2013

In this paper, we establish the existence results for second order singular Dirichlet problems via variational methods. Some recent results are extended and improved. Examples are also given to illustrate the new results.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.963-966
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• 1998

In this paper, a fingerprint classification algorithm is presented. Fingerprint types are classified into five categories: arch, tented arch, left loop, right loop and whorl. Singular points (cores and deltas) are detected using Poincare index on the directional image smoothed by adaptive window size. The method is shown to be robust to the variation of fingerprint image qualaity.

• International Journal of Railway
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• 제2권3호
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• pp.118-123
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• 2009

Railway track alignment Standards set a minimum lenght value for straight and circular alignments (art. 5.2.9.), in order to ensure passenger ride comfort in railway vehicles of which dynamic oscillations will thus have to be limited. The transitions between alignments can cause abrupt changes (usually called discontinuities or singular points of the alignment) of curvature, of rate of change of curvature or of rate of change of cant. A passenger is likely to experience effects due to the excitation of the elastic suspension of the vehicle which generates oscillations that are damped as the vehicle moves away from the singularity. The amplitude of these oscillations should be adequately attenuated by the damping of the suspension system within the interval between two successive singular points, especially to avoid resonances. Therefore minimum lengths between two successive singular points are stated in alignment standards. Nevertheless, these nonnative values can be overly conservative in some cases. As an alternative, track alignment designers could try to assess how much the excitation has been attenuated between two successive singular points and thus assess at which point a new singularity may be present without affecting ride comfort. Although such assessment can be made with commercial SW packages which simulate the dynamic behavior of a vehicle considered as a set of rigid bodies interconnected with elastic elements simulating the suspension systems (such as SIMPACK, ADAMS or VAMPIRE), a simplified and user-friendly computation method (based upon the analytical solution of differential equations governing the phenomenon) is made available in this paper to track design engineers, not always used to working with full dynamic models.

• 한국정보통신학회논문지
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• 제11권1호
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• pp.108-113
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• 2007

지문영상 분류는 특징을 이용하여 여러 가지 유형의 지문영상으로 분류하는 것으로, 지문영상 자동인식시스팀에서 매우 중요하다. 본 논문에서는, 지문영상의 한 점에서의 방향척도를 제안하였다. 이 방향척도는 지문영상의 방향장 영상에서 융선 방향의 변화경로를 상술하는 것으로 지문영상의 각각의 점에 대하여 제안된 방향척도를 계산한다. 제안한 알고리즘을 이용하여 지문영상을 특징점(핵심점과 삼각점)을 정의한 후 유형별로 분류하였다. 또한 개선된 Poincare 지수 알고리즘도 제안하여 핵심점과 삼각점을 구분하였다. 102개의 지문영상 실험 데이터에 대한 분류에러는 7.8%로서 문헌[9]의 분류오차 12.4%보다 좋은 실험결과를 얻을 수 있었다. 또한 제안한 방법은 온라인 지문영상 분류에도 사용가능 할 것으로 생각한다.

• 대한수학회논문집
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• 제30권1호
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• pp.7-21
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• 2015

We give the characterization of H$\ddot{o}$lder differentiability points and non-differentiability points of the Riesz-N$\acute{a}$gy-Tak$\acute{a}$cs (RNT) singular function ${\Psi}_{a,p}$ satisfying ${\Psi}_{a,p}(a)=p$. It generalizes recent multifractal and metric number theoretical results associated with the RNT function. Besides, we classify the singular functions using the singularity order deduced from the H$\ddot{o}$lder derivative giving the information that a strictly increasing smooth function having a positive derivative Lebesgue almost everywhere has the singularity order 1 and the RNT function ${\Psi}_{a,p}$ has the singularity order $g(a,p)=\frac{a{\log}p+(1-a){\log}(1-p)}{a{\log}a+(1-a){\log}(1-a)}{\geq}1$.

• 대한임베디드공학회논문지
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• 제18권3호
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• pp.117-124
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• 2023

In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제11권2호
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• pp.49-57
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• 2007

In fingerprints, singular regions including core or delta points have different directional characteristics from non-singular regions. Generally, the ridges of singular regions change more abruptly than those of nonsingular areas, thus in order to effectively enhance fingerprint images regardless of region, local ridge curvature information needs to be used. In this paper, we present an improved Directional Filter Bank (DFB)-based fingerprint image enhancement method that effectively takes advantage of such ridge curvature information. The proposed method first decomposes a fingerprint image into 8 directional subbands using the DFB and then classifies the image into background, low curvature, and high curvature regions using the directional energy estimates calculated from the subbands. Thereafter, the weight values for directional subband processing are determined using classification information and directional energy estimates. Finally, the enhanced image is obtained by synthesizing the processed subbands. The experimental results show that the proposed approach is effective in enhancing both singular and non-singular regions.

• Journal of applied mathematics & informatics
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• 제27권3_4호
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• pp.621-638
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• 2009

The linear system Ax = b will have (i) no solution, (ii) only one non-trivial (trivial) solution, or (iii) infinity of solutions. Our focus will be on cases (ii) and (iii). The mathematical models of many real-world problems give rise to (a) ill-conditioned linear systems, (b) singular linear systems (A is singular with all its linearly independent rows are sufficiently linearly independent), or (c) ill-conditioned singular linear systems (A is singular with some or all of its strictly linearly independent rows are near-linearly dependent). This article highlights the scope and need of a randomized algorithm for ill-conditioned/singular systems when a reasonably narrow domain of a solution vector is specified. Further, it stresses that with the increasing computing power, the importance of randomized algorithms is also increasing. It also points out that, for many optimization linear/nonlinear problems, randomized algorithms are increasingly dominating the deterministic approaches and, for some problems such as the traveling salesman problem, randomized algorithms are the only alternatives.