• 제목/요약/키워드: local linear method

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Robust Nonparametric Regression Method using Rank Transformation

    • Communications for Statistical Applications and Methods
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    • 제7권2호
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    • pp.574-574
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    • 2000
  • Consider the problem of estimating regression function from a set of data which is contaminated by a long-tailed error distribution. The linear smoother is a kind of a local weighted average of response, so it is not robust against outliers. The kernel M-smoother and the lowess attain robustness against outliers by down-weighting outliers. However, the kernel M-smoother and the lowess requires the iteration for computing the robustness weights, and as Wang and Scott(1994) pointed out, the requirement of iteration is not a desirable property. In this article, we propose the robust nonparametic regression method which does not require the iteration. Robustness can be achieved not only by down-weighting outliers but also by transforming outliers. The rank transformation is a simple procedure where the data are replaced by their corresponding ranks. Iman and Conover(1979) showed the fact that the rank transformation is a robust and powerful procedure in the linear regression. In this paper, we show that we can also use the rank transformation to nonparametric regression to achieve the robustness.

Robust Nonparametric Regression Method using Rank Transformation

  • Park, Dongryeon
    • Communications for Statistical Applications and Methods
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    • 제7권2호
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    • pp.575-583
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    • 2000
  • Consider the problem of estimating regression function from a set of data which is contaminated by a long-tailed error distribution. The linear smoother is a kind of a local weighted average of response, so it is not robust against outliers. The kernel M-smoother and the lowess attain robustness against outliers by down-weighting outliers. However, the kernel M-smoother and the lowess requires the iteration for computing the robustness weights, and as Wang and Scott(1994) pointed out, the requirement of iteration is not a desirable property. In this article, we propose the robust nonparametic regression method which does not require the iteration. Robustness can be achieved not only by down-weighting outliers but also by transforming outliers. The rank transformation is a simple procedure where the data are replaced by their corresponding ranks. Iman and Conover(1979) showed the fact that the rank transformation is a robust and powerful procedure in the linear regression. In this paper, we show that we can also use the rank transformation to nonparametric regression to achieve the robustness.

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블록-순환으로 분배된 배열의 지역 주소 생성 (Generating Local Addresses for Block-Cyclic Distributed Array)

  • 권오영;김태근;한탁돈;양성봉;김신덕
    • 한국정보처리학회논문지
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    • 제5권11호
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    • pp.2835-2844
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    • 1998
  • 대부분의 데이터 병렬 언어들은 배열을 분배하는 방법을 제공하고 있다. 이들 중 블록-순환(block-cyclic) 분배가 가장일반적인 데이터 방법이다. 블록-순환 형태로 분할된 배열 구간 A(l:h:s) 중 각 프로세서가 자신의 메모리 영역에서 접근하는 A의 지역주소를 컴파일러 또는 실시간 시스템들이 생성하는 방안에 대한 연구가 이루어지고 있다. 이 논문에서는 블록-순환 분배된 배열에 대한 두 가지 지역 주소 생성 방법을 제안한다. 하나는 가상-블록 (virtual-block)을 변형한 simple scan 방법이고, 다른 하나는 지역 메모리 접근에 대한 정보를 포함하는 ${\Delta}M$테이블을 선형시간에 생성하는 알고리즘이다. ${\Delta}M$테이블 생성과 각 프로세서가 10,000개의 지역배열 원소를 접근하는데 소요된 시간을 측정하는 실험을 하였다. 실험결과 simple scan 방법은 성능이 좋지 못하였다. 하지만 ${\Delta}M$테이블을 구성하는 다른 방법들 보다 빠른 시간에 수행이 완료되었다.

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선형 제약 만족 최적화 문제를 위한 정수계획법 기반 지역 탐색 기법 (Integer Programming-based Local Search Technique for Linear Constraint Satisfaction Optimization Problem)

  • 황준하;김성영
    • 한국컴퓨터정보학회논문지
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    • 제15권9호
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    • pp.47-55
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    • 2010
  • 선형 제약 만족 최적화 문제는 선형식으로 표현 가능한 목적함수 및 복잡한 제약조건을 포함하는 조합 최적화 문제를 의미한다. 정수계획법은 이와 같은 문제를 해결하는 데 매우 효과적인 기법으로 알려져 있지만 문제의 규모가 커질 경우 준최적해를 도출하기까지 매우 많은 시간과 메모리를 요구한다. 본 논문에서는 지역 탐색과 정수계획법을 결합하여 탐색 성능을 향상할 수 있는 방안을 제시한다. 기본적으로 대상 문제의 해결을 위해 지역 탐색의 가장 단순한 형태인 단순 언덕오르기 탐색을 사용하되 이웃해 생성 시 정수계획법을 적용한다. 또한 부가적으로 초기해 생성을 위해 제약 프로그래밍을 활용한다. N-Queens 최대화 문제를 대상으로 한 실험 결과, 본 논문에서 제시한 기법을 통해 다른 탐색 기법들보다 훨씬 더 좋은 해를 도출할 수 있음을 확인할 수 있었다.

MLR 및 SVR 기반 선형과 비선형회귀분석의 비교 - 풍속 예측 보정 (Comparison of MLR and SVR Based Linear and Nonlinear Regressions - Compensation for Wind Speed Prediction)

  • 김준봉;오승철;서기성
    • 전기학회논문지
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    • 제65권5호
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    • pp.851-856
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    • 2016
  • Wind speed is heavily fluctuated and quite local than other weather elements. It is difficult to improve the accuracy of prediction only in a numerical prediction model. An MOS (Model Output Statistics) technique is used to correct the systematic errors of the model using a statistical data analysis. The Most of previous MOS has used a linear regression model for weather prediction, but it is hard to manage an irregular nature of prediction of wind speed. In order to solve the problem, a nonlinear regression method using SVR (Support Vector Regression) is introduced for a development of MOS for wind speed prediction. Experiments are performed for KLAPS (Korea Local Analysis and Prediction System) re-analysis data from 2007 to 2013 year for Jeju Island and Busan area in South Korea. The MLR and SVR based linear and nonlinear methods are compared to each other for prediction accuracy of wind speed. Also, the comparison experiments are executed for the variation in the number of UM elements.

Improved Dynamic Programming in Local Linear Approximation Based on a Template in a Lightweight ECG Signal-Processing Edge Device

  • Lee, Seungmin;Park, Daejin
    • Journal of Information Processing Systems
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    • 제18권1호
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    • pp.97-114
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    • 2022
  • Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

Design of Sliding Mode Fuzzy-Model-Based Controller Using Genetic Algorithms

  • Chang, Wook
    • 한국지능시스템학회논문지
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    • 제11권7호
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    • pp.615-620
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    • 2001
  • This paper addresses the design of sliding model fuzzy-model-based controller using genetic algorithms. In general, the construction of fuzzy logic controllers has difficulties for the lack of systematic design procedure. To release this difficulties, the sliding model fuzzy-model-based controllers was presented by authors. In this proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Although, the stability and the performance is guaranteed by the proposed method, some design parameters have to be chosen by the designer manually. This problem can be solved by using genetic algorithms. The proposed method tunes the parameters of the controller, by which the reasonable accuracy and the control effort is achieved. The validity and the efficiency of the proposed method are verified through simulations.

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Pseudo plastic zone analysis of steel frame structures comprising non-compact sections

  • Avery, P.;Mahendran, M.
    • Structural Engineering and Mechanics
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    • 제10권4호
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    • pp.371-392
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    • 2000
  • Application of "advanced analysis" methods suitable for non-linear analysis and design of steel frame structures permits direct and accurate determination of ultimate system strengths, without resort to simplified elastic methods of analysis and semi-empirical specification equations. However, the application of advanced analysis methods has previously been restricted to steel frames comprising only compact sections that are not influenced by the effects of local buckling. A concentrated plasticity method suitable for practical advanced analysis of steel frame structures comprising non-compact sections is presented in this paper. The pseudo plastic zone method implicitly accounts for the effects of gradual cross-sectional yielding, longitudinal spread of plasticity, initial geometric imperfections, residual stresses, and local buckling. The accuracy and precision of the method for the analysis of steel frames comprising non-compact sections is established by comparison with a comprehensive range of analytical benchmark frame solutions. The pseudo plastic zone method is shown to be more accurate and precise than the conventional individual member design methods based on elastic analysis and specification equations.

IEEE 802.11n 기반 MIMO-IC의 간섭정렬 성능평가 (Evaluation of Interference Alignment for MIMO-IC based on IEEE 802.11n)

  • 배인산;윤희석;김재명
    • 한국위성정보통신학회논문지
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    • 제8권4호
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    • pp.47-52
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    • 2013
  • 본 논문에서는, 기존에 연구되었던 간섭정렬 기법들은 주로 레일레이 채널 환경에서 분석이 이뤄졌다. 간섭정렬 기법은 크게 Iterative-method와 Linear-method로 구분되어 지며, Iterative-method는 반복이라는 제약이 있지만 채널정보가 적게 드는 장점이 있다. Linear-method은 광역 채널 정보(global channel info)가 필요하지만 반복에서 자유로우며 비교적 성능이 우수하다. 이 논문에서는 기존의 간섭정렬 기법들을 실외 환경의 레일리에 패이딩 채널과 실내 환경인 IEEE 802.11n 채널에 적용함으로써 성능을 비교하고자 한다.