• 제목/요약/키워드: sparse matrix

검색결과 253건 처리시간 0.032초

공학문제 해결을 위한 프로그램에서의 재사용이 가능한 Matrix의 효율적 자동생성기법 (An efficient technique to generate reusable matrix to solve a problem in the engineering field)

  • 이미영
    • 정보처리학회논문지D
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    • 제10D권7호
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    • pp.1145-1148
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    • 2003
  • 공학문제 해결을 위한 수치적 프로그램에서 원하는 해와 그 해의 변이 값에 대하여 같은 수준의 오차를 유지할 수 있는 기존의 복합유한 요소방법을 소개하고 이에 대한 효과적인 프로그램 재사용을 이용한 Matrix 생성기법을 소개한다. 또한, 원하는 임의의 차수의 기저에 대한 Matrix의 자동 생성기법을 제안한다. 여기서, 자동 생성된 Matrix는 최소한의 nonzero element를 갖고, 이는 Inverse Matriix 형성에 있어서 최소오차와 효율성을 보장한다. 위에서 제안한 MatriBt 생성기법을 최소표면적 문제에 적용하여 본다.

THE EXISTENCE THEOREM OF ORTHOGONAL MATRICES WITH p NONZERO ENTRIES

  • CHEON, GI-SANG;LEE, SANG-GU;SONG, SEOK-ZUN
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제4권1호
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    • pp.109-119
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    • 2000
  • It was shown that if Q is a fully indecomposable $n{\times}n$ orthogonal matrix then Q has at least 4n-4 nonzero entries in 1993. In this paper, we show that for each integer p with $4n-4{\leq}p{\leq}n^2$, there exist a fully indecomposable $n{\times}n$ orthogonal matrix with exactly p nonzero entries. Furthermore, we obtain a method of construction of a fully indecomposable $n{\times}n$ orthogonal matrix which has exactly 4n-4 nonzero entries. This is a part of the study in sparse matrices.

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Newton-Krylov Method for Compressible Euler Equations on Unstructured Grids

  • Kim Sungho;Kwon Jang Hyuk
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 1998년도 추계 학술대회논문집
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    • pp.153-159
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    • 1998
  • The Newton-Krylov method on the unstructured grid flow solver using the cell-centered spatial discretization oi compressible Euler equations is presented. This flow solver uses the reconstructed primitive variables to get the higher order solutions. To get the quadratic convergence of Newton method with this solver, the careful linearization of face flux is performed with the reconstructed flow variables. The GMRES method is used to solve large sparse matrix and to improve the performance ILU preconditioner is adopted and vectorized with level scheduling algorithm. To get the quadratic convergence with the higher order schemes and to reduce the memory storage. the matrix-free implementation and Barth's matrix-vector method are implemented and compared with the traditional matrix-vector method. The convergence and computing times are compared with each other.

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웨이블릿을 이용한 파수영역 전자파 산란 해석법 연구 (A Study of Spectral Domain Electromagnetic Scattering Analysis Applying Wavelet Transform)

  • 빈영부;주세훈;이정흠;김형동
    • 한국전자파학회논문지
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    • 제11권3호
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    • pp.337-344
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    • 2000
  • 파수영역에서 모멘트법의 엄피던스 행렬의 특정을 관찰하고 이를 웨이블릿 변환을 이용하여 효율적으로 표현 하는 방법을 연구하였다. 영상 선호처리 분야에서 자주 사용되는 이차원 쿼드트리(2-D Quadtree)방법(행렬의 $\phi$ 부분에만 웨이블릿 변환을 적용하는 방법)을 적용하여 모멘트 행렬을 성기게 만들었다. 웨이블릿이 적용된 모멘트 행렬을 CG( Conjugate-Gradient)법을 이용하여 모멘트 법의 계산량과 메모리를 줄였다. 수치적 결과는 정사 각형 실린더의 경우 임피던스 행렬의 0이 아닌 값이 O($N^{1.6}$)으로 증가하는 것을 관찰하였다.

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PERFORMANCE COMPARISON OF PRECONDITIONED ITERATIVE METHODS WITH DIRECT PRECONDITIONERS

  • Yun, Jae Heon;Lim, Hyo Jin;Kim, Kyoum Sun
    • Journal of applied mathematics & informatics
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    • 제32권3_4호
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    • pp.389-403
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    • 2014
  • In this paper, we first provide comparison results of preconditioned AOR methods with direct preconditioners $I+{\beta}L$, $I+{\beta}U$ and $I+{\beta}(L+U)$ for solving a linear system whose coefficient matrix is a large sparse irreducible L-matrix, where ${\beta}$ > 0. Next we propose how to find a near optimal parameter ${\beta}$ for which Krylov subspace method with these direct preconditioners performs nearly best. Lastly numerical experiments are provided to compare the performance of preconditioned iterative methods and to illustrate the theoretical results.

희소성 음향 통신 채널 추정 견실화를 위한 백색화를 적용한 l1놈-RLS 알고리즘 (L1 norm-recursive least squares algorithm for the robust sparse acoustic communication channel estimation)

  • 임준석;편용국;김성일
    • 한국음향학회지
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    • 제39권1호
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    • pp.32-37
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    • 2020
  • 본 논문은 l1놈-Recursive Least Squares(RLS)에 수치 계산상 견실화를 더한 새로운 알고리즘을 제안한다. Eksioglu와 Tanc는 희소성 음향 채널 추정을 위해서 l1놈-RLS 알고리즘을 구현하였다. 그러나 이 알고리즘의 근간인 RLS 계산법 역행렬 계산에서 수치 계산상의 불안정성을 지니고 있다. 본 논문에서는 이런 불안정성을 낮추는 새로운 알고리즘을 제안한다. 그리고 제안한 방법을 사용했을 때 수치적 불안정성에 대한 성능이 개선되었음을 보인다.

Dynamic Synchronous Phasor Measurement Algorithm Based on Compressed Sensing

  • Yu, Huanan;Li, Yongxin;Du, Yao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권1호
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    • pp.53-76
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    • 2020
  • The synchronous phasor measurement algorithm is the core content of the phasor measurement unit. This manuscript proposes a dynamic synchronous phasor measurement algorithm based on compressed sensing theory. First, a dynamic signal model based on the Taylor series was established. The dynamic power signal was preprocessed using a least mean square error adaptive filter to eliminate interference from noise and harmonic components. A Chirplet overcomplete dictionary was then designed to realize a sparse representation. A reduction of the signal dimension was next achieved using a Gaussian observation matrix. Finally, the improved orthogonal matching pursuit algorithm was used to realize the sparse decomposition of the signal to be detected, the amplitude and phase of the original power signal were estimated according to the best matching atomic parameters, and the total vector error index was used for an error evaluation. Chroma 61511 was used for the output of various signals, the simulation results of which show that the proposed algorithm cannot only effectively filter out interference signals, it also achieves a better dynamic response performance and stability compared with a traditional DFT algorithm and the improved DFT synchronous phasor measurement algorithm, and the phasor measurement accuracy of the signal is greatly improved. In practical applications, the hardware costs of the system can be further reduced.

다중 후보 매칭 퍼슛 (Multiple Candidate Matching Pursuit)

  • 권석법;심병효
    • 방송공학회논문지
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    • 제17권6호
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    • pp.954-963
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    • 2012
  • Orthogonal matching pursuit (OMP) 알고리듬은 underdetermined 시스템에서 희소 신호를 복구하는 대표적인 greedy 알고리듬으로 많은 관심을 받고 있다. 본 논문에서는 OMP 알고리듬의 반복과정에서 후보 support 집합들을 구성하여 마지막 반복과정에서 최소 잔차를 이용하는 multiple candidate matching pursuit (MuCaMP) 기법을 제안한다. MuCaMP 가 완벽한 신호 복원을 보장하기 위한 restricted isometry property (RIP)를 이용한 충분조건, ${\delta}_{N+K}<\frac{\sqrt{N}}{\sqrt{K}+3\sqrt{N}}$을 제시한다. 실험을 통해 후보 support 집합들의 크기에 따른 성능과 MuCaMP의 복원 성능이 기존의 기법들에 비해 우수함을 확인하였다.

Why Gabor Frames? Two Fundamental Measures of Coherence and Their Role in Model Selection

  • Bajwa, Waheed U.;Calderbank, Robert;Jafarpour, Sina
    • Journal of Communications and Networks
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    • 제12권4호
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    • pp.289-307
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    • 2010
  • The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

Joint Estimation of TOA and DOA in IR-UWB System Using Sparse Representation Framework

  • Wang, Fangqiu;Zhang, Xiaofei
    • ETRI Journal
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    • 제36권3호
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    • pp.460-468
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    • 2014
  • This paper addresses the problem of joint time of arrival (TOA) and direction of arrival (DOA) estimation in impulse radio ultra-wideband systems with a two-antenna receiver and links the joint estimation of TOA and DOA to the sparse representation framework. Exploiting this link, an orthogonal matching pursuit algorithm is used for TOA estimation in the two antennas, and then the DOA parameters are estimated via the difference in the TOAs between the two antennas. The proposed algorithm can work well with a single measurement vector and can pair TOA and DOA parameters. Furthermore, it has better parameter-estimation performance than traditional propagator methods, such as, estimation of signal parameters via rotational invariance techniques algorithms matrix pencil algorithms, and other new joint-estimation schemes, with one single snapshot. The simulation results verify the usefulness of the proposed algorithm.