• Journal of Information Processing Systems
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• 제13권6호
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• pp.1585-1601
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• 2017

With the rapid development of computer technologies, a number of image modification methods have emerged, which have great impacts on the security of image information. Therefore, it is necessary to protect the integrity and authenticity of digital images, and digital watermarking technique consequently becomes a research hotspot. An effort is made to survey and analyze advancements of image watermarking algorithms based on singular value decomposition (SVD) in recent years. In the first part, an overview of watermarking techniques is presented and then mathematical theory of SVD is given. Besides, SVD watermarking model, features, and evaluation indexes are demonstrated. Various SVD-based watermarking algorithms, as well as hybrid watermarking algorithms based on SVD and other transforms for copyright protection, tamper detection, location, and recovery are reviewed in the last part.

• 한국정밀공학회지
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• 제16권2호통권95호
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• pp.116-122
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• 1999

저차 동적계(특히 카오스계)에서 측정한 시계열의 잡음을 제거하기 위해서 SVD(Singular Value Decomposotion)을 이용한 새로운 간편하고 매우 효과적인 새로운 잡음 제거법이 소개되었다. 이 방법은 위상궤적(phase portraint)을 재구성하는데 중점을 두었으며, 궤적행렬(trajectory matrix)을 구성하는데 그 기본을 두었다. 이 궤적행렬에 SVD를 반복적으로 사용하여 신호와 잡음을 분리하였다. 이 방법은 Duffing계에서 측정한 잡음이 섞인 카오스 신호에 적용되었으며, 또한 실험에 의한 진폭변조된 신호에도 적용되었다.

• 한국항해항만학회지
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• 제38권2호
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• pp.89-96
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• 2014

This paper presents an improvement for calculating method of astronomical ship position based on circle of equal altitude equation. In addition, to enhance the accuracy of ship position achieved from solving equation system, the authors used singular value decomposition (SVD) in least square method instead of normal decomposition. In maths, the SVD was proved more numerically stable than normal decomposition. Therefore, the solution of equation system will be more efficient and the result would be more accurate than previous methods. By proposal algorithm, a computer program have been developed to help the navigators in calculating directly ship position when the modern equipment has failure. Finally, some of experiments are carried out to verify effectiveness of proposed algorithm, the results show that the accuracy of ship position based on new method is better than the intercept method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1762-1765
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• 1997

Some ill-conditioned processes are very sensitive to small element-wise uncertainties arising in classical element-by-element model identifications. For such processes, accurate identification of simgular values and right singular vectors are more important than theose of the elements themselves. Singular values and right singular vectors can be found by iteraive identification methods which implement the input and output transformations iteratively. Methods based on SVD decomposition, QR decomposition and LU decomposition are proposed and compared with the Kuong and Mac Gregor's method. Convergence proofs are given. These SVD and QR mehtods use normal matrices for the transformations which cannot be calculated analytically in general and so they are hoard to apply to dynamic processes, whereas the LU method used simple analyitc transformations and can be directly applied to dynamic processes.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.275-288
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• 2023

Many image edge details are easily lost in the image denoising process, and the smooth image regions are prone to produce jagged. In this paper, we propose a wavelet-based image global k- singular value decomposition variational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noise of low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes the random noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value is higher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that the proposed method can effectively suppress image noise while retaining more image edge details. The denoised image has better denoising effects.

• 대한전자공학회논문지
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• 제17권3호
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• pp.20-25
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• 1980

Singular value decomposition을 통한 pseudo-inverse를 단층영상 재구성에 이용하였다. 본 논문에서는 SVD pseudo-inverse를 이용한 truncated inverse filter와 Scalar Wiener filter에 대하여 검토하고 각각에 대하여 통계적 측면에서의 최적화가 연구되었다. 이러한 방법은 신호와 잡음문에 trade-off를 기함으로써 재구성 문제에 항상 뒤따르는 ill-conditioning 현상을 극복할 수 있다. 본 논문을 통하여 구성된 filter의 성능을 확인하기 위하여 컴퓨터를 이용한 simulation이 이루어졌으며 그 결과 재구성된 협상은 만족할 만 하였다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제29권4호
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• pp.248-257
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• 2002

군집화는 객체들의 특성을 분석하여 유사한 성질을 갖고 있는 객체들을 동일한 집단으로 분류하는 방법이다. 전자 상거래 자료처럼 차원 수가 많고 누락 값이 많은 자료의 경우 입력 자료의 차원축약, 잡음제거를 목적으로 SVD를 사용하여 군집화를 수행하는 것이 효과적이지만, SVD를 통해 변환된 자료는 원래의 속성 정보를 상실하기 때문에 군집 결과분석에서 원본 속성의 가치 해석이 어렵다. 따라서 본 연구는 군집화 수행 후 엔트로피 가중치 및 SVD를 이용하여 군집의 중요한 속성을 발견하기 위한 군집 특징 선택 기법 ENTROPY-SVD를 제안한다. ENTROPY-SVD는 자료의 속성들과 유사객체 군과의 묵시적인 은닉 구조를 활용하기 위하여 SVD를 이용하고 유사객체 군에 포함된 응집도가 높은 속성들을 발견하기 위하여 엔트로피 가중치를 사용한다. 또한 ENTROPY-SVD를 적용한 모델 기반의 협력적 여과기법의 추천 시스템 CFS-CF를 제안하고 그 효용성 및 효과를 평가한다.

• International Journal of Control, Automation, and Systems
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• 제5권5호
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• pp.508-514
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• 2007

Properties and potential applications of the block pulse response circulant matrix (PRCM) and its singular value decomposition (SVD) are investigated in relation to MIMO control and identification. The SVD of the PRCM is found to provide complete directional as well as frequency decomposition of a MIMO system in a real matrix form. Three examples were considered: design of MIMO FIR controller, design of robust reduced-order model predictive controller, and input design for MIMO identification. The examples manifested the effectiveness and usefulness of the PRCM in the design of MIMO control and identification. irculant matrix, SVD, MIMO control, identification.

• 한국산업정보학회논문지
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• 제15권2호
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• pp.49-57
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• 2010

본 논문에서는 역전파 신경망 알고리즘(BPNN: Back Propagation Neural Network)과 Singular Value Decomposition(SVD)를 이용하는 한글 문서 분류 시스템을 제안한다. BPNN은 학습을 통하여 만들어진 네트워크를 이용하여 문서분류를 수행한다. 이 방법의 어려움은 분류기에 입력되는 특징 공간이 너무 크다는 것이다. SVD를 이용하면 고차원의 벡터를 저차원으로 줄일 수 있고, 또한 의미있는 벡터 공간을 만들어 단어 사이의 중요한 관계성을 구축할 수 있다. 본 논문에서 제안한 BPNN의 성능 평가를 위하여 한국일보-2000/한국일보-40075 문서범주화 실험문서집합의 데이터 셋을 이용하였다. 실험결과를 통하여 BPNN과 SVD를 사용한 시스템이 한글 문서 분류에 탁월한 성능을 가지는 것을 보여준다.

• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.413-419
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• 1998

A novel order-reduction technique for model predictive control(MPC) is proposed based on the singular value decomposition(SVD) of a pulse response circulant matrix(PRCM) of a concerned system. It is first investigated that the PRCM (in the limit) contains a complete information of the frequency response of a system and its SVD decomposes the information into the respective principal directions at each frequency. This enables us to isolate the significant modes of the system and to devise the proposed order-reduction technique. Though the primary purpose of the proposed technique is to diminish the required computation in MPC, the clear frequency decomposition of the SVD of the PRCM also enables us to improve the robustness through selective excitation of frequency modes. Performance of the proposed technique is illustrated through two numerical examples.