• Title/Summary/Keyword: 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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    • v.14 no.3
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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.

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

  • Moon, Won Sik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.3
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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.

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

  • Lee, Bong-Hwan
    • The Transactions of the Korea Information Processing Society
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    • v.1 no.3
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    • pp.380-390
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    • 1994
  • In this paper, we propose an equal-cost bifurcated routing algorithm which may be useful in practical computer network design problem. The performance of the routing algorithm is evaluated using the conventional Monte Carlo simulation and a transient queueing approximation. The relative errors between the closure approximation and the Monte Carlo simulation was fairly small. The closure approximation may be used to evaluate the performance of the load splitting algorithms, which results in considerable execution time reduction. The performance of the proposed algorithm is compared to that of the known algorithms based on average packet delay. For networks that have many non-disjoint equal-paths, the proposed algorithm performed better than other algorithms.

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A NOTE ON GREEDY ALGORITHM

  • Hahm, Nahm-Woo;Hong, Bum-Il
    • Bulletin of the Korean Mathematical Society
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    • v.38 no.2
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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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Efficient LDPC Decoding Algorithm Using Node Monitoring (노드 모니터링에 의한 효율적인 LDPC 디코딩 알고리듬)

  • Suh, Hee-Jong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.11
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    • pp.1231-1238
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    • 2015
  • In this paper, we proposed an efficient algorithm using Node monitoring (NM) and Piecewise Linear Function Approximation(: NP) for reducing the complexity of LDPC code decoding. Proposed NM algorithm is based on a new node-threshold method together with message passing algorithm. Piecewise linear function approximation is used to reduce the complexity of the algorithm. This new algorithm was simulated in order to verify its efficiency. Complexity of our new NM algorithm is improved to about 20% compared with well-known methods according to simulation results.

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

  • Nam, Haewon
    • Journal of Biomedical Engineering Research
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    • v.41 no.1
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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.

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

  • Song, Ha-Joo;Kwon, Oh-Heum
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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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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    • v.27 no.1
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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 Algorithm with Piecewise Linear Function Approximation for Efficient LDPC Decoding (Node Monitoring 알고리듬과 NP 방법을 사용한 효율적인 LDPC 복호방법)

  • Suh, Hee-Jong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.6 no.1
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    • pp.20-26
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    • 2011
  • In this paper, we propose an efficient algorithm for reducing the complexity of LDPC code decoding by using node monitoring (NM) and Piecewise Linear Function Approximation (NP). This NM algorithm is based on a new node-threshold method, and the message passing algorithm. Piecewise linear function approximation is used to reduce the complexity for more. This algorithm was simulated in order to verify its efficiency. Simulation results show that the complexity of our NM algorithm is reduced to about 20%, compared with thoes of well-known method.

A Study on Tool Interference Avoidance Using Rectangular Surface Approximation (가각근사에 의한 공구 간섭 제거에 관한 연구)

  • 장동규;이희관;양균의
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.188-192
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    • 1994
  • This paper presenta new method for tool interference acoidance using rectanguar approximation in NC machining of scuptured surface. The procedure of algorithm for approximation of sculptured surface to rectangular surface is described. Using this algorithm, we can check concave, convex, and side interference region and avoid these interferenes.

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