• ETRI Journal
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• 제40권5호
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• pp.634-642
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• 2018

Projection spectral analysis is investigated and refined in this paper, in order to unify principal component analysis and independent component analysis. Singular value decomposition and spectral theorems are applied to nonsymmetric correlation or covariance matrices with multiplicities or singularities, where projections and nilpotents are obtained. Therefore, the suggested approach not only utilizes a sum-product of orthogonal projection operators and real distinct eigenvalues for squared singular values, but also reduces the dimension of correlation or covariance if there are multiple zero eigenvalues. Moreover, incremental learning strategies of projection spectral analysis are also suggested to improve the performance.

• 방송공학회논문지
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• 제21권2호
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• pp.149-156
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• 2016

우리는 컨텐츠 복제방지를 위하여 기존의 SVD와 DWT/RDWT를 결합한 워터마킹 시스템에 특이벡터를 추가로 사용하는 방안을 제안하였다. 우리는 SVD를 사용하는 워터마킹 시스템에 존재하는 오류긍정문제(false-positive problem)를 극복하기 위하여 기존의 SVD기반 알고리즘과 같이 특이값에 워트마크를 임베딩할 뿐만 아니라, 커버이미지의 첫 번째 좌/우 특이벡터를 워터마크 이미지의 첫번째 좌/우 특이벡터와 교체하였다. 제안 방안은 오류긍정문제 (false-positive problem)가 발생하지 않는 워터마킹 시스템을 구현할 수 있었으며, 기존의 오류긍정문제가 없는 시스템과 비교하여 우수한 충실성과 강인성을 보여 주었을 뿐만 아니라, 오류긍정문제가 발생하는 시스템에 비해서도 크게 성능차이가 나지 않음을 보여 주었다.

• 한국정보통신학회논문지
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• 제11권5호
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• pp.997-1003
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• 2007

이 논문에서는 LCD에 사용되는 편광필름 영상에서 결함을 검출하는 방법을 제안하였다. 제안한 방법은 결함의 지엽적인 특징을 이용하는 것이 아니라 특이값 분해를 이용하여 영상의 전역적인 정보를 반영하는 방법이다. 편광필름 영상을 특이값 분해하고 특이값 중에서 첫 번째 특이값만을 사용하여 영상을 재구성하면 재구성한 영상에서 정상 부분의 화소값과 결함 부분의 화소값들은 서로 다른 특성을 나타낸다. 입력 영상과 재구성한 영상의 화소값 비를 구하고 확률론적 방법을 사용하여 결함을 검출하였다. 제안한 방법을 이용하여 여러 가지 결함을 갖는 편광필름 영상에서 결함을 검출한 결과 검출력이 매우 우수한 것으로 나타났다.

• 한국인터넷방송통신학회논문지
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• 제15권5호
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• pp.39-49
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• 2015

Jacket Matrices: Construction and Its Application for Fast Cooperative Wireless signal Processing[27]에 소개된 Jacket 행렬로부터 일반화된 의사 Jacket 행렬에 대한 특성과 생성에 관한 정리가 발표됐다. 본 논문에서는 MIMO 채널과 같이 $2{\times}4$, $3{\times}6$ 같은 비정방 행렬에서의 의사 Jacket 역행렬에 대한 예제를 제안했다. 또한 의사 MIMO 특이값 분해 (SVD, Singular Value Decomposition) channel을 추론하여 적용하였으며 안테나 어레이를 분할하여 추정하는 채널을 기반으로 SVD를 활용하는데 적용하였다. 이것은 MIMO 채널 및 고유값 분해 (EVD, Eigen Value decomposition) 등에 사용할 수 있다.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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• pp.267-271
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• 2007

본 논문은 원본이미지와 은닉이미지의 좋은 압축률과 만족할만한 이미지의 질, 그리고 외부공격에 강인한 이미지은닉의 한 방법으로 특이치 분해와 퍼지 군집화를 이용한 벡터양자화를 이용한 워터마킹 방법을 소개하였다. 실험에서는 은닉된 이미지의 비가시성과 외부공격에 대한 강인성을 증명하였다.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.766-776
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• 2015

It is well known that series arc faults in Low Voltage DC (LVDC) distribution system occur at unintended points of discontinuity within an electrical circuit. These faults can make circuit breakers not respond timely due to low fault current. It, therefore, is needed to detect the series fault for protecting circuits from electrical fires. This paper proposes a novel scheme to detect the series arc fault using Wavelet Singular Value Decomposition (WSVD) and state diagram. In this paper, the fault detector developed is designed by using three criterion factors based on the RMS value of Singular value of Approximation (SA), Sum of the absolute value of Detail (SD), and state diagram. LVDC distribution system including AC/DC and DC/DC converter is modeled to verify the proposed scheme using ElectroMagnetic Transient Program (EMTP) software. EMTP/MODELS is also utilized to implement the series arc model and WSVD. Simulation results according to various conditions clearly show the effectiveness of the proposed scheme.

• 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.

• ETRI Journal
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• 제33권4호
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• pp.652-655
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• 2011

In this letter, we propose a new compression method for a high dimensional support vector machine (SVM). We used singular value decomposition (SVD) to compress the norm part of a radial basis function SVM. By deleting the least significant vectors that are extracted from the decomposition, we can compress each vector with minimized energy loss. We select the compressed vector dimension according to the predefined threshold which can limit the energy loss to design criteria. We verified the proposed vector compressed SVM (VCSVM) for conventional datasets. Experimental results show that VCSVM can reduce computational complexity and memory by more than 40% without reduction in accuracy when classifying a 20,958 dimension dataset.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1170-1178
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• 2021

This paper proposed a versatile algorithm based on a dual-tree complex wavelet transform for intensifying the visual aspect of medical images. First, the decomposition of the input image into a high sub-band and low-sub-band image is done. Further, to improve the resolution of the resulting image, the high sub-band image is interpolated using Lanczos interpolation. Also, contrast enhancement is performed by singular value decomposition (SVD). Finally, the image reconstruction is achieved by using an inverse wavelet transform. Then, the Gaussian filter will improve the visual quality of the image. We have collected images from the hospital and the internet for quantitative and qualitative analysis. These images act as a reference image for comparing the effectiveness of the proposed algorithm with the existing state-of-the-art. We have divided the proposed algorithm into several stages: preprocessing, contrast enhancement, resolution enhancement, and visual quality enhancement. Both analyses show the proposed algorithm's effectiveness compared to existing methods.

• 한국소음진동공학회논문집
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• 제11권9호
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• pp.431-438
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• 2001

This paper present experimental results of source identification for non-minimum phase system. Generally, a causal linear system may be described by matrix form. The inverse problem is considered as a matrix inversion. Direct inverse method can\`t be applied for a non-minimum phase system, the reason is that the system has ill-conditioning. Therefore, in this study to execute an effective inversion, SVD inverse technique is introduced. In a Non-minimum phase system, its system matrix may be singular or near-singular and has one more very small singular values. These very small singular values have information about a phase of the system and ill-conditioning. Using this property we could solve the ill-conditioned problem of the system and then verified it for the practical system(cantilever beam). The experimental results show that SVD inverse technique works well for non-minimum phase system.