• 제목/요약/키워드: Approximation algorithm

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Moment-Based Density Approximation Algorithm for Symmetric Distributions

  • Ha, Hyung-Tae
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.583-592
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    • 2007
  • Given the moments of a symmetric random variable, its density and distribution functions can be accurately approximated by making use of the algorithm proposed in this paper. This algorithm is specially designed for approximating symmetric distributions and comprises of four phases. This approach is essentially based on the transformation of variable technique and moment-based density approximants expressed in terms of the product of an appropriate initial approximant and a polynomial adjustment. Probabilistic quantities such as percentage points and percentiles can also be accurately determined from approximation of the corresponding distribution functions. This algorithm is not only conceptually simple but also easy to implement. As illustrated by the first two numerical examples, the density functions so obtained are in good agreement with the exact values. Moreover, the proposed approximation algorithm can provide the more accurate quantities than direct approximation as shown in the last example.

확장된 근사 알고리즘을 이용한 조합 방법 (Rule of Combination Using Expanded Approximation Algorithm)

  • 문원식
    • 디지털산업정보학회논문지
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    • 제9권3호
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    • pp.21-30
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    • 2013
  • Powell-Miller theory is a good method to express or treat incorrect information. But it has limitation that requires too much time to apply to actual situation because computational complexity increases in exponential and functional way. Accordingly, there have been several attempts to reduce computational complexity but side effect followed - certainty factor fell. This study suggested expanded Approximation Algorithm. Expanded Approximation Algorithm is a method to consider both smallest supersets and largest subsets to expand basic space into a space including inverse set and to reduce Approximation error. By using expanded Approximation Algorithm suggested in the study, basic probability assignment function value of subsets was alloted and added to basic probability assignment function value of sets related to the subsets. This made subsets newly created become Approximation more efficiently. As a result, it could be known that certain function value which is based on basic probability assignment function is closely near actual optimal result. And certainty in correctness can be obtained while computational complexity could be reduced. by using Algorithm suggested in the study, exact information necessary for a system can be obtained.

클로즈 근사화를 이용한 등가 라우팅 알고리즘의 설계 (Design of Equal-Cost Bifurcated Routing Algorithm : A Case Study Using Closure Approximation)

  • 이봉환
    • 한국정보처리학회논문지
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    • 제1권3호
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    • pp.380-390
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    • 1994
  • 본 논문에서는 컴퓨터 네트워크의 설계에 유용한 등가 라우팅 알고리즘(Equal- cost Bifurcated Routing Algorithm)을 제안하였다. 이 제안한 알고리즘의 성능은 기존의 몬테카를로 시뮬레이션 및 비정상 큐잉 근사화(Transient queueing approximation)를 이용하여 비교되었으며 그 결과 큐잉 근사화는 몬테카를로 시뮬레이 션에 상당히 근접한 결과를 제공하였다. 또한, 큐잉 근사화는 몬테카를로 시뮬레이션 에 비하여 매우 적은 수행시간을 요구하므로 제안한 등가 라우팅 알고리즘은 대부분 의 경우에 우수한 결과를 제공하였다.

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A NOTE ON GREEDY ALGORITHM

  • Hahm, Nahm-Woo;Hong, Bum-Il
    • 대한수학회보
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    • 제38권2호
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    • pp.293-302
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    • 2001
  • We improve the greedy algorithm which is one of the general convergence criterion for certain iterative sequence in a given space by building a constructive greedy algorithm on a normed linear space using an arithmetic average of elements. We also show the degree of approximation order is still $Ο(1\sqrt{\n}$) by a bounded linear functional defined on a bounded subset of a normed linear space which offers a good approximation method for neural networks.

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노드 모니터링에 의한 효율적인 LDPC 디코딩 알고리듬 (Efficient LDPC Decoding Algorithm Using Node Monitoring)

  • 서희종
    • 한국전자통신학회논문지
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    • 제10권11호
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    • pp.1231-1238
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    • 2015
  • 본 논문에서는 노드 모니터링(NM)과 Piecewise Linear Function Approximation(: NP)을 사용하여 LDPC 디코딩 알고리듬의 계산복잡도를 감소시키는 알고리듬을 제안한다. 이 알고리듬은 기존의 알고리듬보다도 더 효율적이다. 제안된 알고리즘이 기존의 방법보다도 개선되었다는 것을 확인하기 위해서 모의실험을 하였다. 실험결과, 제안된 알고리즘의 계산은 기존의 방법에 비해 약 20 % 향상되었음을 확인하였다.

완전 데이터 적응형 MLS 근사 알고리즘을 이용한 Interleaved MRI의 움직임 보정 알고리즘 (Motion Artifact Reduction Algorithm for Interleaved MRI using Fully Data Adaptive Moving Least Squares Approximation Algorithm)

  • 남혜원
    • 대한의용생체공학회:의공학회지
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    • 제41권1호
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    • pp.28-34
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    • 2020
  • In this paper, we introduce motion artifact reduction algorithm for interleaved MRI using an advanced 3D approximation algorithm. The motion artifact framework of this paper is data corrected by post-processing with a new 3-D approximation algorithm which uses data structure for each voxel. In this study, we simulate and evaluate our algorithm using Shepp-Logan phantom and T1-MRI template for both scattered dataset and uniform dataset. We generated motion artifact using random generated motion parameters for the interleaved MRI. In simulation, we use image coregistration by SPM12 (https://www.fil.ion.ucl.ac.uk/spm/) to estimate the motion parameters. The motion artifact correction is done with using full dataset with estimated motion parameters, as well as use only one half of the full data which is the case when the half volume is corrupted by severe movement. We evaluate using numerical metrics and visualize error images.

First-fit 전략을 사용하는 템플럿 패킹 문제를 위한 근사 알고리즘 (An Approximation Algorithm based on First-fit Strategy for Template Packing Problem)

  • 송하주;권오흠
    • 한국멀티미디어학회논문지
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    • 제19권2호
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    • pp.443-450
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    • 2016
  • This paper deals with a kind of packing problem of which the goal is to compose one or more templates which will be used to produce the items of different types. Each template consists of a fixed number of slots which are assigned to the different types of items and the production of the items is accomplished by printing the template repeatedly. The objective is to minimize the total number of produced items. This problem is known to be NP-hard. We present a polynomial time approximation algorithm which has a constant approximation ratio. The proposed algorithm is based on the well-known first-fit strategy.

An efficient algorithm for the non-convex penalized multinomial logistic regression

  • Kwon, Sunghoon;Kim, Dongshin;Lee, Sangin
    • Communications for Statistical Applications and Methods
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    • 제27권1호
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    • pp.129-140
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    • 2020
  • In this paper, we introduce an efficient algorithm for the non-convex penalized multinomial logistic regression that can be uniformly applied to a class of non-convex penalties. The class includes most non-convex penalties such as the smoothly clipped absolute deviation, minimax concave and bridge penalties. The algorithm is developed based on the concave-convex procedure and modified local quadratic approximation algorithm. However, usual quadratic approximation may slow down computational speed since the dimension of the Hessian matrix depends on the number of categories of the output variable. For this issue, we use a uniform bound of the Hessian matrix in the quadratic approximation. The algorithm is available from the R package ncpen developed by the authors. Numerical studies via simulations and real data sets are provided for illustration.

Node Monitoring 알고리듬과 NP 방법을 사용한 효율적인 LDPC 복호방법 (Node Monitoring Algorithm with Piecewise Linear Function Approximation for Efficient LDPC Decoding)

  • 서희종
    • 한국전자통신학회논문지
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    • 제6권1호
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    • pp.20-26
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    • 2011
  • 본 논문에서는 NM(node monitoring) 알고리듬과 NP(Piecewise Linear Function Approximation)를 사용해서 LDPC 코드 복호의 복잡도를 감소시키기 위한 효율적인 알고리듬을 제안한다. 이 NM 알고리듬은 새로운 node-threshold 방법과 message passing 알고리듬에 근거해서 제안되었는데, 이에 NP 방법을 사용해서 알고리듬의 복잡도를 더 줄일 수 있었다. 이 알고리듬의 효율성을 입증하기 위해서 모의 실험을 하였다. 모의실험결과, 기존에 잘 알려진 방법에 비해서 20% 정도 더 효율적이었다.

직교설 전후방 PAST (Projection Approximation Subspace Tracking) 알고리즘 (Orthonormalized Forward Backward PAST (Projection Approximation Subspace Tracking) Algorithm)

  • 임준석
    • 한국음향학회지
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    • 제28권6호
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    • pp.514-519
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    • 2009
  • PAST (projection approximation subspace tracking)는 여러 연구자들에 의해 비교 연구가 되는 대표적인 신호 부공간을 추정하는 알고리즘이다. 이 방법은 신호 부공간 추정에 있어 상대적으로 낮은 계산 복잡도를 요구하기 때문에 인기가 있는 방법이 되었다. 그러나 이 방법은 개선의 여지가 많아서 추정 정확도나 공간의 직교성 등에서 계속 개선된 알고리즘이 연구되고 있다. 본 논문은 기존에 연구된 PAST 알고리즘의 추정 정확도 개선을 위해 연구된 알고리즘 중 하나인 FB-PAST(Forward-Backward PAST) 알고리즘에 사용할 직교성 알고리즘을 제안한다.