• 제목/요약/키워드: Singular value decomposition

검색결과 369건 처리시간 0.032초

SVD 및 트리플릿 기반의 디지털 워터마킹 기법 (Digital Watermarking Scheme based on SVD and Triplet)

  • 박병수;추형석;안종구
    • 전기학회논문지
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    • 제58권5호
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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.

SVD Pseudo-inverse를 이용한 영상 재구성 (SVD Pseudo-inverse and Application to Image Reconstruction from Projections)

  • 심영석;김성필
    • 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.

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텐세그러티 구조의 외력에 대한 적정 프리스트레스 결정 (Optimal prestress of Tensegrity Structures for External Load)

  • 안정태;이재홍
    • 한국공간구조학회논문집
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    • 제13권1호
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    • pp.59-67
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    • 2013
  • This paper presents a new numerical method to analyse tensegrity structures by using singular value decomposition and force method. The tensegrity system consisting of compressive and tensle elements are pin-jointed system. Tensegrity structures, unlike the general structure should be preceded by form-finding. Tensegrity structures form-finding of the self-equilibrium stress stability, seeking to have the process. In this study, tensegrity structures when subjected to external loads, find the optimal pre-stress values was studied.

A Coupled Recursive Total Least Squares-Based Online Parameter Estimation for PMSM

  • Wang, Yangding;Xu, Shen;Huang, Hai;Guo, Yiping;Jin, Hai
    • Journal of Electrical Engineering and Technology
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    • 제13권6호
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    • pp.2344-2353
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    • 2018
  • A coupled recursive total least squares (CRTLS) algorithm is proposed for parameter estimation of permanent magnet synchronous machines (PMSMs). TLS considers the errors of both input variables and output ones, and thus achieves more accurate estimates than standard least squares method does. The proposed algorithm consists of two recursive total least squares (RTLS) algorithms for the d-axis subsystem and q-axis subsystem respectively. The incremental singular value decomposition (SVD) for the RTLS obtained by an approximate calculation with less computation. The performance of the CRTLS is demonstrated by simulation and experimental results.

Mode-SVD-Based Maximum Likelihood Source Localization Using Subspace Approach

  • Park, Chee-Hyun;Hong, Kwang-Seok
    • ETRI Journal
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    • 제34권5호
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    • pp.684-689
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    • 2012
  • A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

An Identification Technique Based on Adaptive Radial Basis Function Network for an Electronic Odor Sensing System

  • Byun, Hyung-Gi
    • 센서학회지
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    • 제20권3호
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    • pp.151-155
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    • 2011
  • A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

Tensor-based tag emotion aware recommendation with probabilistic ranking

  • Lim, Hyewon;Kim, Hyoung-Joo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권12호
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    • pp.5826-5841
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    • 2019
  • In our previous research, we proposed a tag emotion-based item recommendation scheme. The ternary associations among users, items, and tags are described as a three-order tensor in order to capture the emotions in tags. The candidates for recommendation are created based on the latent semantics derived by a high-order singular value decomposition technique (HOSVD). However, the tensor is very sparse because the number of tagged items is smaller than the amount of all items. The previous research do not consider the previous behaviors of users and items. To mitigate the problems, in this paper, the item-based collaborative filtering scheme is used to build an extended data. We also apply the probabilistic ranking algorithm considering the user and item profiles to improve the recommendation performance. The proposed method is evaluated based on Movielens dataset, and the results show that our approach improves the performance compared to other methods.

자기상관유사행렬을 이용한 과도기적 신호의 분석 (Analysis of Transient Signal Using Autocorrelation-like Matrix)

  • 최규성;김영수
    • 한국통신학회논문지
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    • 제23권7호
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    • pp.1689-1698
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    • 1998
  • 본 논문에서는 잡음환경하에서의 과도기형태 신호의 매개변수를 효율적으로 추정하기 위한 새로운 방법을 제안한다. 이 방법은 선형예측모델을 토대로 하여 확장된 차수를 갖는 자기상관유사행렬의 truncated singular value decomposition을 이용한다. 제안된 자기상관유사행렬의 우수성을 보여주기 위하여 감쇄계수가 같은 경우와 감쇄계수가 다른 경우에 대하여 각각 일반적인 데이터 행렬방법과 통계적 성능을 비교분석하였다. 시뮬레이션 결과 데이터 행렬 방법보다 자기상관유사행렬 방법의 통계적 성능이 보다 우수함을 알 수 있었다. 이러한 결과는 부가된 백색잡음의 자기상관지연값이 클 경우에 잡음의 영향이 어느정도 줄어든다는 성질로 부터 기인한다.

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Spatial Multiuser Access for Reverse Link of Multiuser MIMO Systems

  • 신오순
    • 한국통신학회논문지
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    • 제33권10A호
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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.

DNA칩 데이터 분석을 위한 유전자발연 통합분석 프로그램의 개발 (Program Development of Integrated Expression Profile Analysis System for DNA Chip Data Analysis)

  • 양영렬;허철구
    • KSBB Journal
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    • 제16권4호
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    • pp.381-388
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    • 2001
  • DNA칩의 유전자 발현 데이터의 통합적 분석을 위하여 매트랩을 기반으로 한 통합분석 프로그램을 구축하였다. 이 프로그램은 유전자 발현 분석을 위해 일반적으로 많이 쓰는 방법인 Hierarchical clustering(HC), K-means, Self-organizing map(SOM), Principal component analysis(PCA)를 지원하며, 이외에 Fuzzy c-means방법과 최근에 발표된 Singular value decomposition(SVD) 분석 방법도 지원하고 있다. 통합분석프로그램의 성능을 알아보기 위하여 효모의 포자형성(sporulation)과 정의 유전자발현 데이터를 사용하였으며, 각 분석 방법에 따른 분석 결과를 제시하였으며, 이 프로그램이 유전자 발현데이타의 통합적인 분석을 위해 효과적으로 사용될 수 있음을 제시하였다.

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