• Title/Summary/Keyword: Singular value

검색결과 568건 처리시간 0.024초

Transmit Antenna Selection for Dual Polarized Channel Using Singular Value Decision

  • Lee Sang-yub;Mun Cheol;Yook Jong-gwan
    • 한국통신학회논문지
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    • 제30권9A호
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    • pp.788-794
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    • 2005
  • In this paper, we focus on the potential of dual polarized antennas in mobile system. thus, this paper designs exact dual polarized channel with Spatial Channel Model (SCM) and investigates the performance for certain environment. Using proposed the channel model; we know estimates of the channel capacity as a function of cross polarization discrimination (XPD) and spatial fading correlation. It is important that the MIMO channel matrix consists of Kronecker product dividable spatial and polarized channel. Through the channel characteristics, we propose an algorithm for the adaptation of transmit antenna configuration to time varying propagation environments. The optimal active transmit antenna subset is determined with equal power allocated to the active transmit antennas, assuming no feedback information on types of the selected antennas. We first consider a heuristic decision strategy in which the optimal active transmit antenna subset and its system capacity are determined such that the transmission data rate is maximized among all possible types. This paper then proposes singular values decision procedure consisting of Kronecker product with spatial and polarize channel. This method of singular value decision, which the first channel environments is determined using singular values of spatial channel part which is made of environment parameters and distance between antennas. level of correlation. Then we will select antenna which have various polarization type. After spatial channel structure is decided, we contact polarization types which have considerable cases It is note that the proposed algorithms and analysis of dual polarized channel using SCM (Spatial Channel Model) optimize channel capacity and reduce the number of transmit antenna selection compare to heuristic method which has considerable 100 cases.

SOLVING SINGULAR NONLINEAR TWO-POINT BOUNDARY VALUE PROBLEMS IN THE REPRODUCING KERNEL SPACE

  • Geng, Fazhan;Cui, Minggen
    • 대한수학회지
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    • 제45권3호
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    • pp.631-644
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    • 2008
  • In this paper, we present a new method for solving a nonlinear two-point boundary value problem with finitely many singularities. Its exact solution is represented in the form of series in the reproducing kernel space. In the mean time, the n-term approximation $u_n(x)$ to the exact solution u(x) is obtained and is proved to converge to the exact solution. Some numerical examples are studied to demonstrate the accuracy of the present method. Results obtained by the method are compared with the exact solution of each example and are found to be in good agreement with each other.

Vision Based Map-Building Using Singular Value Decomposition Method for a Mobile Robot in Uncertain Environment

  • Park, Kwang-Ho;Kim, Hyung-O;Kee, Chang-Doo;Na, Seung-Yu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.101.1-101
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    • 2001
  • This paper describes a grid mapping for a vision based mobile robot in uncertain indoor environment. The map building is a prerequisite for navigation of a mobile robot and the problem of feature correspondence across two images is well known to be of crucial Importance for vision-based mapping We use a stereo matching algorithm obtained by singular value decomposition of an appropriate correspondence strength matrix. This new correspondence strength means a correlation weight for some local measurements to quantify similarity between features. The visual range data from the reconstructed disparity image form an occupancy grid representation. The occupancy map is a grid-based map in which each cell has some value indicating the probability at that location ...

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Noise Suppression of NMR Signal by Piecewise Polynomial Truncated Singular Value Decomposition

  • Kim, Daesung;Youngdo Won;Hoshik Won
    • 한국자기공명학회논문지
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    • 제4권2호
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    • pp.116-124
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    • 2000
  • Singular value decomposition (SVD) has been used during past few decades in the advanced NMR data processing and in many applicable areas. A new modified SVD, piecewise polynomial truncated SVD (PPTSVD) was developed far the large solvent peak suppression and noise elimination in U signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L$_1$ problems. In TSVD, some unwanted large solvent peaks and noises are suppressed with a certain son threshold value while signal and noise in raw data are resolved and eliminated out in L$_1$ problem routine. The advantage of the current PPTSVD method compared to many SVD methods is to give the better S/N ratio in spectrum, and less time consuming job that can be applicable to multidimensional NMR data processing.

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부채널 분석 성능향상을 위한 특이값분해 신호처리 기법에 관한 연구 (Study on Singular Value Decomposition Signal Processing Techniques for Improving Side Channel Analysis)

  • 박건민;김태원;김희석;홍석희
    • 정보보호학회논문지
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    • 제26권6호
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    • pp.1461-1470
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    • 2016
  • 부채널 분석에서 신호처리 기법은 차원 압축이나 잡음 제거를 통해 분석의 효율성과 성능을 높일 수 있는 전처리 기법이다. 특이값 분해를 이용한 신호처리 방법은 신호의 분산 정보나 경향성 등을 이용하여 주 신호 정보를 높이고 잡음신호를 낮출 수 있어, 분석 성능 향상에 큰 도움이 된다. 대표적인 기법은 주성분분석과 선형판별분석 그리고 Singular Spectrum Analysis(SSA)가 있다. 주성분분석과 선형판별분석은 주 신호의 정보를 집약하여 차원 압축을 할 수 있으며, SSA는 본 신호를 주 신호와 잡음 신호로 분해하여 잡음 제거가 가능하다. 세 가지 기법 각각을 사용하거나 조합하여 사용할 경우 성능적인 측면을 비교할 필요가 있으며, 그에 대한 방법론이 필요하다. 본 논문에서는 세 기법을 개별적으로 사용할 경우와 조합하여 사용할 경우의 성능을 비교 분석하였으며, 신호 대 잡음비를 이용한 비교분석 방법론을 제시하였다. 제시한 방법론과 다양한 비교분석 실험을 통해 각 기법의 성능과 효율성을 확인하였다. 이로 인해 부채널 분석 분야의 많은 연구자들에게 유용한 정보를 제공할 것이다.

MULTIPLE SOLUTIONS OF IMPULSIVE BOUNDARY VALUE PROBLEMS ON THE HALF-LINE

  • Liu, Xiyu;Yan, Baoqiang
    • Journal of applied mathematics & informatics
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    • 제5권1호
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    • pp.111-124
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    • 1998
  • Existence results of multiple solutions are obtained un-der suitable conditions for impulsive integrodifferential boundary value problems on the half-line which may be singular at the boundary.

특이치 분해와 Fuzzy C-Mean(FCM) 군집화를 이용한 벡터양자화에 기반한 워터마킹 방법 (An Watermarking Method based on Singular Vector Decomposition and Vector Quantization using Fuzzy C-Mean Clustering)

  • 이병희;장우석;강환일
    • 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.

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