• Korean Journal of Optics and Photonics
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• v.4 no.4
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• pp.363-372
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• 1993

An optimization technique with variable orthogonalization and SVD(singular value decomposition) is examined in a double-Gauss type photographic lens design and its convergence and stability are compared with ordinary least squares and DLS(damped least squares) method. It is known that there are close relationship between the stability of optimization and condition number of nomal equation, the ratio between maximum and minimum of eigenvalues. In this study, the stability is greatly improved by limiting the condition number, the SVD, as expeded. The case of DLS with small damping, orthogonalization and SVD shows the most rapid convergence and stability. It means that the unstability of DLS method with small damping is overcome by using the variable orthogonalization and SVD.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.49-57
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• 2010

This paper proposes a Korean document. categorization algorithm using Back Propagation Neural Network(BPNN) with Singular Value Decomposition(SVD). BPNN makes a network through its learning process and classifies documents using the network. The main difficulty in the application of BPNN to document categorization is high dimensionality of the feature space of the input documents. SVD projects the original high dimensional vector into low dimensional vector, makes the important associative relationship between terms and constructs the semantic vector space. The categorization algorithm is tested and compared on HKIB-20000/HKIB-40075 Korean Text Categorization Test Collections. Experimental results show that BPNN algorithm with SVD achieves high effectiveness for Korean document categorization.

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.289-298
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• 2008

We propose an SNR-scalable coding algorithm for three-dimensional mesh sequences based on singular value decomposition (SVD). SVD achieves a coding gain by representing a mesh sequence with a small number of basis vectors and singular values. First, we introduce a bit plane coding scheme and derive a quantitative relationship between each bit plane and the reconstructed image quality. Using the relationship, we develop a rate-distortion (RD) optimized coding algorithm. Moreover, we propose prediction techniques to exploit the spatio-temporal correlations in real mesh sequences. Simulation results demonstrate that the proposed algorithm provides significantly better RD performance than conventional SVD coders.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.82-86
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• 2006

The design of a pattern recognition system generally involves the three aspects: preprocessing, feature extraction, and decision making. Among them, a feature extraction method determines an appropriate subspace of dimensionality in the original feature space of dimensionality so that it can reduce the complexity of the system and help to improve successful recognition rates. Linear transforms, such as principal component analysis, factor analysis, and linear discriminant analysis have been widely used in pattern recognition for feature extraction. This paper shows that singular value decomposition (SVD) can be applied usefully in feature extraction stage of pattern recognition. As an application, a remote sensing problem is applied to verify the usefulness of SVD. The experimental result indicates that the feature extraction using SVD can improve the recognition rate about 25% compared with that of PCA.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.302-308
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• 2001

SVD(Singular Value Decomposition) filter for the suppression of EMG in multi-lead stress ECG is studied. SVD filter consists of two parts. In the first part, the basis vectors were chosen from the averaged singular vectors obtained from the decomposed noise-free ECG. The singular vector is computed from the stress ECG and is compared itself with basis vectors to know whether the noise exist in stress ECG. In the second part, the existing elimination method is used, when one(or two) channels is(or are) contaminated by noise. But the proposed enhanced SVD filter is used in case of having the noise in the many channels. During signal decomposition and reconstruction, the noise-free channel or the least noisy channel have the weight of 1, the next less noisy channel has the weight of 0.8. In this way, every channel was weighted by decreased of 0.2 in proportion to the amount of the added noise. For the evaluation of the proposed enhanced SVD filter, we compared the SNR computed by the enhanced SVD filter with the standard average filter for the noise-free signal added with artificial noise and the patient data. The proposed SVD filter showed better in the SNR than the standard average filter. In conclusion, we could find that the enhanced SVD filter is more proper in processing multi-lead stress ECG.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1041-1046
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• 2009

In this paper, we proposed a robust watermark scheme for image based on SVD(Singular Value Transform) and Triplet. First, the original image is decomposed by using 3-level DWT, and then used the singular values changed for embedding and extracting of the watermark sequence in LL3 band. Since the matrix of singular values is not easily altered with various signal processing noises, the embedded watermark sequence has the ability to withstand various signal processing noise attacks. Nevertheless, this method does not guarantee geometric transformation(such as rotation, cropping, etc.) because the geometric transformation changes the matrix size. In this case, the watermark sequence cannot be extracted. To compensate for the above weaknesses, a method which uses the triplet for embedding a barcode image watermark in the middle of frequency band is proposed. In order to generate the barcode image watermark, the pattern of the watermark sequence embedded in a LL3 band is used. According to this method, the watermark information can be extracted from attacked images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.980-986
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• 2008

Spatial multiuser access is investigated for the reverse link of multiuser multiple-input multiple-output (MIMO) systems. In particular, we consider two alternative a aches to spatial multiuser access that adopt the same detection algorithm at the base station: one is a closed-loop approach based on singular value decomposition (SVD) of the channel matrix, whereas the other is an open-loop approach based in space-time block coding (STBC). We develop multiuser detection algorithms for these two spatial multiuser access schemes based on the minimum mean square error (MMSE) criterion. Then, we compare the bit error rate (BER) performance of the two schemes and a single-user MIMO scheme. Interestingly, it is found that the STBC approach can provide much better BER performance than the SVD approach as well as than a single-user MIMO scheme.

• KSBB Journal
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• v.16 no.4
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• pp.381-388
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• 2001

A program for integrated gene expression profile analysis such as hierarchical clustering, K-means, fuzzy c-means, self-organizing map(SOM), principal component analysis(PCA), and singular value decomposition(SVD) was made for DNA chip data anlysis by using Matlab. It also contained the normalization method of gene expression input data. The integrated data anlysis program could be effectively used in DNA chip data analysis and help researchers to get more comprehensive analysis view on gene expression data of their own.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.51-52
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• 2011

본 논문에서는 WT(Wavelet Transform)와 SVD(Singular Value Decomposition)기법을 결합한 WSVD(Wavelet Singular Value Decomposition)를 사용하여, 송전계통에서 부하 탈락 시 나타나는 특성 및 외란검출의 유효성을 분석하였다. WSVD 방식을 이용한 외란검출을 모의하기 위해 EMTP-RV를 이용하여 부산 및 경남 일부지역 345kV급 송전계통을 모델링하였고, 이 계통에서 부하 탈락을 모의하였다. WSVD의 계산은 MATLAB을 통해 수행하였으며, 이 결과를 바탕으로 전력계통에서 부하 탈략량의 변화에 따른 특징을 분석하였다

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.244-245
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• 2011

In this paper, the algorithm for detecting load shedding based on Wavelet Singular Value Decomposition(WSVD) is proposed. WSVD is method of signal processing which combine Wavelet Transform(WT) and Singular Value Decomposition(SVD) to analyze transients in power system. 345kV Busan transmission system is modeled by EMTP-RV and simulations according to successive change of load capability are conducted. This paper analyzes characteristics of WSVD by using simulation results and proposes algorithm for detecting load shedding.