• Communications for Statistical Applications and Methods
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• v.17 no.6
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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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• 2005.10a
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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.

• Journal of the Korean Mathematical Society
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• v.50 no.4
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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.

• Proceedings of the IEEK Conference
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• 1998.10a
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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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• v.2 no.3
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.108-113
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• 2007

The classification of fingerprint images is to classify fingerprint images into varies fingerprint types, it is very important in automatic fingerprint recognition. In this paper, a new singular points detection technique was presented. A direction uniform measure is defined to describe the changes of direction fields in a certain neighborhood of fingerprint images. Singular points can be detected by adopting the measure. It should be pointed out that singular points in accurate positions would be obtained in this ways. And an improved Poincare exponential algorithm is presented to identify core points and triangle points. In this paper. making use of 102 experimental fingerprint images datas and attained 7.8% classification errors. This was better than experimental result of abstract [9]. It is possible to use on-line fingerprint images classification.

• Communications of the Korean Mathematical Society
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• v.30 no.1
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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 $g(a,p)=\frac{a{\log}p+(1-a){\log}(1-p)}{a{\log}a+(1-a){\log}(1-a)}{\geq}1$.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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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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• v.11 no.2
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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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• v.27 no.3_4
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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.