• 제목/요약/키워드: vector approximation

검색결과 185건 처리시간 0.019초

Conservative Approximation-Based Full-Search Block Matching Algorithm Architecture for QCIF Digital Video Employing Systolic Array Architecture

  • Ganapathi, Hegde;Amritha, Krishna R.S.;Pukhraj, Vaya
    • ETRI Journal
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    • 제37권4호
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    • pp.772-779
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    • 2015
  • This paper presents a power-efficient hardware realization for a motion estimation technique that is based on the full-search block matching algorithm (FSBMA). The considered input is the quarter common intermediate format of digital video. The mean of absolute difference (MAD) is the distortion criteria employed for the block matching process. The conventional architecture considered for the hardware realization of FSBMA is that of the shift register-based 2-D systolic array. For this architecture, a conservative approximation technique is adapted to eliminate unnecessary MAD computations involved in the block matching process. Upon introducing the technique to the conventional architecture, the power and complexity of its implantation is reduced, while the accuracy of the motion vector extracted from the block matching process is preserved. The proposed architecture is verified for its functional specifications. A performance evaluation of the proposed architecture is carried out using parameters such as power, area, operating frequency, and efficiency.

VA-Tree : 대용량 데이터를 위한 효율적인 다차원 색인구조 (VA-Tree : An Efficient Multi-Dimensional Index Structure for Large Data Set)

  • 송석일;이석희;조기형;유재수
    • 한국멀티미디어학회논문지
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    • 제6권5호
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    • pp.753-768
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    • 2003
  • 이 논문은 다차원의 특징벡터를 벡터 근사치로 표현한 후 색인 트리를 구성하여 검객의 효율을 높이는 VA(Vector Approximate)-트리를 제안한다. 이 논문에서 제안하는 VA-트리는 전체적인 색인구조의 저장 공간을 줄이기 위해서 VA-화일의 벡터 근사치 개념을 이용하여 데이터양이 증가해도 검색 성능이 저하되지 않도록 하는 트리 형태의 구조를 갖는다. VA-트리는 MBR 기반의 색인구조이지만 MBR간에 겹침이 발생하지 않는 분할 방법을 사용하여 검색 효율을 높인다. 제안하는 색인구조와 기존의 여러 다차원 색인구조와의 성능 평가를 통해 제안하는 방법의 우수함을 보인다.

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서포트벡터 기계를 이용한 이상치 진단 (Outlier Detection Using Support Vector Machines)

  • 서한손;윤민
    • Communications for Statistical Applications and Methods
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    • 제18권2호
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    • pp.171-177
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    • 2011
  • 실생활에서 얻어지는 자료에서 근사함수를 구성하기 위하여 모델링을 하기 전에 측정된 원자료로부터 이상치를 제거하는 것이 필요하다. 기존의 이상치 진단의 방법들은 시각화나 최대 잔차들을 이용해왔다. 그러나 종종 다차원의 입력자료를 가지는 비선형함수에 대한 이상치 진단은 좋지 않은 결과를 얻었다. 다차원 입력자료를 갖는 비선형함수에 대한 전형적인서포트 벡터 회귀에 기초한 이상치 진단방법들은 좋은 수행능력을 얻어지지만, 계산비용이나 모수들의 보정 등의 실질적인 문제점들을 가지고 있다. 본 논문에서 계산비용을 감소하고 이상치의 문턱을 적절히 정의하는 서포트 벡터회귀를 이용한 이상치 진단의 실질적인방법을 제안한다. 제안한 방법을 실제자료들에 적용하여 타당성을 보일 것이다.

A PATH-SWITCHING STRATEGY BY COMBINING THE USE OF GENERALIZED INVERSE AND LINE SEARCH

  • Choong, K.K.;Hangai, Y.;Kwun, T.J.
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1994년도 봄 학술발표회 논문집
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    • pp.95-102
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    • 1994
  • A path-switching strategy by combining the use of generalized inverse and line search is proposed. A reliable predictor for the tangent vector to bifurcation path is first computed by using the generalized inverse approach. A line search in the direction of maximum gradient of total potential at the point of intersection between the above predictor and a constant loading plane introduced in the vicinity of the detected bifurcation point is then carried out for the purpose of obtaining an improved approximation for a point on bifurcation path. With this approximation obtained, an actual point on bifurcation path is then computed through iteration on the constant loading plane.

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근사 선탐색을 이용한 동적 반응 최적화 (Dynamic response optmization using approximate search)

  • 김민수;최동훈
    • 대한기계학회논문집A
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    • 제22권4호
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    • pp.811-825
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    • 1998
  • An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.

부구조화 기반 전역-부분 근사화 구조재해석에 의한 구조최적화 (Structural Optimization by Global-Local Approximations Structural Reanalysis based on Substructuring)

  • 김태봉;서상구;김창운
    • 한국안전학회지
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    • 제12권3호
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    • pp.120-131
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    • 1997
  • This paper presents an approximate reanalysis methods of structures based on substructuring for an effective optimization of large-scale structural systems. In most optimal design procedures the analysis of the structure must be repeated many times. In particular, one of the main obstacles in the optimization of structural systems are involved high computational cost and expended long time in the optimization of large-scale structures. The purpose of this paper is to evaluate efficiently the structural behavior of new designs using information from previous ones, without solving basic equations for successive modification in the optimal design. The proposed reanalysis procedure is combined Taylor series expansions which is a local approximation and reduced basis method which is a global approximation based on substructuring. This technique is to choose each of the terms of Taylor series expansions as the basis vector of reduced basis method in substructuring system which is one of the most effective analysis of large -scale structures. Several numerical examples illustrate the effectiveness of the solution process.

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무선통신에서의 Non-Linear Detector System 설계 (The System of Non-Linear Detector over Wireless Communication)

  • 공형윤
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.106-109
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    • 1998
  • Wireless communication systems, in particular, must operate in a crowded electro-magnetic environmnet where in-band undesired signals are treated as noise by the receiver. These interfering signals are often random but not Gaussian Due to nongaussian noise, the distribution of the observables cannot be specified by a finite set of parameters; instead r-dimensioal sample space (pure noise samples) is equiprobably partitioned into a finite number of disjointed regions using quantiles and a vector quantizer based on training samples. If we assume that the detected symbols are correct, then we can observe the pure noise samples during the training and transmitting mode. The algorithm proposed is based on a piecewise approximation to a regression function based on quantities and conditional partition moments which are estimated by a RMSA (Robbins-Monro Stochastic Approximation) algorithm. In this paper, we develop a diversity combiner with modified detector, called Non-Linear Detector, and the receiver has a differential phase detector in each diversity branch and at the combiner each detector output is proportional to the second power of the envelope of branches. Monte-Carlo simulations were used as means of generating the system performance.

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점성 및 비점성 유동장 해석을 위한 BGK 수치기법의 효율적 계산 (Efficient Calculation of Gas-kinetic BGK scheme for Analysis of Inviscid and Viscous Flows)

  • 채동석;김종암;노오현
    • 한국전산유체공학회지
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    • 제3권2호
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    • pp.65-72
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    • 1998
  • From the Boltzmann equation with BGK approximation, a gas-kinetic BGK scheme is developed and methods for its efficient calculation, using the convergence acceleration techniques, are presented in a framework of an implicit time integration. The characteristics of the original gas-kinetic BGK scheme are improved in order for the accurate calculation of viscous and heat convection problems by considering Osher's linear subpath solutions and Prandtl number correction. Present scheme applied to various numerical tests reveals a high level of accuracy and robustness and shows advantages over flux vector splittings and Riemann solver approaches from Euler equations.

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Restricted maximum likelihood estimation of a censored random effects panel regression model

  • Lee, Minah;Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • 제26권4호
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    • pp.371-383
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    • 2019
  • Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

구속조건식이 있는 비선형 최적화 문제를 위한 ALM방법의 성능향상 (Computational enhancement to the augmented lagrange multiplier method for the constrained nonlinear optimization problems)

  • 김민수;김한성;최동훈
    • 대한기계학회논문집
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    • 제15권2호
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    • pp.544-556
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    • 1991
  • The optimization of many engineering design problems requires a nonlinear programming algorithm that is robust and efficient. A general-purpose nonlinear optimization program IDOL (Interactive Design Optimization Library) is developed based on the Augmented Lagrange Mulitiplier (ALM) method. The ideas of selecting a good initial design point, using resonable initial values for Lagrange multipliers, constraints scaling, descent vector restarting, and dynamic stopping criterion are employed for computational enhancement to the ALM method. A descent vector is determined by using the Broydon-Fletcher-Goldfarb-Shanno (BFGS) method. For line search, the Incremental-Search method is first used to find bounds on the solution, then the bounds are reduced by the Golden Section method, and finally a cubic polynomial approximation technique is applied to locate the next design point. Seven typical test problems are solved to show IDOL efficient and robust.