• 제목/요약/키워드: Weighted Linear Combination

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Linear Combination of Weighted Order Statistic 필터의 분석과 구현 (Analysis and Implementation of Linear Combination of Weighted Order Statistic Filters)

  • 송종환;이용훈
    • 전자공학회논문지B
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    • 제31B권2호
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    • pp.21-27
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    • 1994
  • Linear combination of weighted order statistic(LWOS) filters, which is an extension of stack filters, can represent any Boolean function(BF) or its extension. Which is called the extended BF(EBF). In this paper, we present a procedure for finding an LWOS filter of the simplest type from LWOS filters which are equivalent to a given BF or EBF. In addition, a property that is useful for implementing an LWOS filter is derived and an algorithm for LWOS filtering is presented.

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Generalized Weighted Linear Models Based on Distribution Functions

  • Yeo, In-Kwon
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2003년도 추계 학술발표회 논문집
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    • pp.161-166
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    • 2003
  • In this paper, a new form of generalized linear models is proposed. The proposed models consist of a distribution function of the mean response and a weighted linear combination of distribution functions of covariates. This form addresses a structural problem of the link function in the generalized linear models. Markov chain Monte Carlo methods are used to estimate the parameters within a Bayesian framework.

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A Study on the Optimum Scheme for Determination of Operation Time of Line Feeders in Automatic Combination Weighers

  • Keraita James N.;Kim Kyo-Hyoung
    • Journal of Mechanical Science and Technology
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    • 제20권10호
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    • pp.1567-1575
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    • 2006
  • In an automatic combination weigher, the line feeders distribute the product to several weighing hoppers. The ability to supply appropriate amount of product to the weighing hoppers for each combination operation is crucial for the overall performance. Determining the right duration of operating a line feeder to supply a given amount of product becomes very challenging in case of products which are irregular in volume or specific gravity such as granular secondary processed foods. In this research, several schemes were investigated to determine the best way for a line feeder to approximate the next operating time in order to supply a set amount of irregular goods to the corresponding weighing hopper. Results obtained show that a weighted least squares method (WLS) employing 10 data points is the most effective in determining the operating times of line feeders.

분포함수를 기초로 일반화가중선형모형 (Generalized Weighted Linear Models Based on Distribution Functions - A Frequentist Perspective)

  • 여인권
    • 응용통계연구
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    • 제17권3호
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    • pp.489-498
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    • 2004
  • 이 논문에서는 일반화가중선형모형이라는 새로운 형태의 선형모형을 제시한다. 일반화가중선형모형은 설명변수와 반응변수의 관계를 설명분포함수의 선형결합이 반응변수의 평균에 대한 연결분포함수를 통해 모형화 되는 형태를 가지는 것으로 가정한다. 이모형은 일반화선형 모형에서 연결함수를 선택할 때 발생할 수 있는 모수공간과 선형 예측값의 공간이 일치하지 않을 수 있다는 문제가 발생하지 않고 모수에 대한 해석이 용이하다는 장점이 있다. 이 논문에서는 설명분포함수와 연결분포함수를 선택하는데 있어 발생할 수 있는 문제와 해결책에 대해 알아본다. 또한 모형에 포함되어 있는 모수를 추정하는데 고려해야 할 주의 사항과 이 사항들을 고려한 최대가능도추정법과 재표집 방법을 이용한 구간추정과 가설검정에 대해 알아본다.

New Adaptive Linear Combination Structure for Tracking/Estimating Phasor and Frequency of Power System

  • Wattanasakpubal, Choowong;Bunyagul, Teratum
    • Journal of Electrical Engineering and Technology
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    • 제5권1호
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    • pp.28-35
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    • 2010
  • This paper presents new Adaptive Linear Combination Structure (ADALINE) for tracking/estimating voltage-current phasor and frequency of power system. To estimate the phasors and frequency from sampled data, the algorithm assumes that orthogonal coefficients and speed of angular frequency of power system are unknown parameters. With adequate sampled data, the estimation problem can be considered as a linear weighted least squares (LMS) problem. In addition to determining the phasors (orthogonal coefficients), the procedure estimates the power system frequency. The main algorithm is verified through a computer simulation and data from field. The proposed algorithm is tested with transient and dynamic behaviors during power swing, a step change of frequency upon islanding of small generators and disconnection of load. The algorithm shows a very high accuracy, robustness, fast response time and adaptive performance over a wide range of frequency, from 10 to 2000 Hz.

국부 통계를 기반으로 한 가중차수 통계의 데이터 의존 선형조합 필터링(DD-LWOS) (Data Department Linear Combination of Weighted Order Statistics(DD-LWOS) Filtering Based on Local Statistics)

  • 박동희;배철수
    • 한국정보통신학회논문지
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    • 제6권4호
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    • pp.639-644
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    • 2002
  • 순위 차수 정보와 공간정보를 이용하는 비선형 필터들은 부가 잡음에 의해 발생되는 불안정 신호를 복원하기 위해서 많이 제안되고 있으면 본 논문에서는 국부통계를 기반으로 계수 변화를 하는 데이터 의존 LWOS필터를 제안하고자 한다. LWOS필터[1]는 가우시안 형태의 잡음뿐만 아니라 미세한 신호를 보호하면서 비임펄스 잡음을 제거할 수 있었으며, 임펄스 잡음에 의해서 방해를 받을 때는 DD-LWOS 필터보다 DD-LWOS2 필터가 더 좋은 결과를 가진다는 것을 확인할 수 있었다.

Developing a Method to Define Mountain Search Priority Areas Based on Behavioral Characteristics of Missing Persons

  • Yoo, Ho Jin;Lee, Jiyeong
    • 한국측량학회지
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    • 제37권5호
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    • pp.293-302
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    • 2019
  • In mountain accident events, it is important for the search team commander to determine the search area in order to secure the Golden Time. Within this period, assistance and treatment to the concerned individual will most likely prevent further injuries and harm. This paper proposes a method to determine the search priority area based on missing persons behavior and missing persons incidents statistics. GIS (Geographic Information System) and MCDM (Multi Criteria Decision Making) are integrated by applying WLC (Weighted Linear Combination) techniques. Missing persons were classified into five types, and their behavioral characteristics were analyzed to extract seven geographic analysis factors. Next, index values were set up for each missing person and element according to the behavioral characteristics, and the raster data generated by multiplying the weight of each element are superimposed to define models to select search priority areas, where each weight is calculated from the AHP (Analytical Hierarchy Process) through a pairwise comparison method obtained from search operation experts. Finally, the model generated in this study was applied to a missing person case through a virtual missing scenario, the priority area was selected, and the behavioral characteristics and topographical characteristics of the missing persons were compared with the selected area. The resulting analysis results were verified by mountain rescue experts as 'appropriate' in terms of the behavior analysis, analysis factor extraction, experimental process, and results for the missing persons.

변형된 상승여현 보간법의 제안과 영상처리에의 응용 (Modified Raised-Cosine Interpolation and Application to Image Processing)

  • 하영호;김원호;김수중
    • 대한전자공학회논문지
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    • 제25권4호
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    • pp.453-459
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    • 1988
  • A new interpolation function, named modified raised-cosine interpolation, is proposed. This function is derived from the linear combination of weighted triangular and raised-cosine functions to reduce the effect of side lobes which incur the interpolation error. Interpolation error reduces significantly for higher-order convolutional interpolation functions of linear operators, but at the expense of resolution error due to the attenuation of main lobe. However, the proposed interpolation function enables us to reduce the side lobes as well as to preserve the main lobe. To prove practicality, this function is applied in image reconstruction and enlargement.

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퍼지 결합 다항식 뉴럴 네트워크 기반 패턴 분류기 설계 (The Design of Pattern Classification based on Fuzzy Combined Polynomial Neural Network)

  • 노석범;장경원;안태천
    • 전기학회논문지
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    • 제63권4호
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    • pp.534-540
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    • 2014
  • In this paper, we propose a fuzzy combined Polynomial Neural Network(PNN) for pattern classification. The fuzzy combined PNN comes from the generic TSK fuzzy model with several linear polynomial as the consequent part and is the expanded version of the fuzzy model. The proposed pattern classifier has the polynomial neural networks as the consequent part, instead of the general linear polynomial. PNNs are implemented by stacking the simple polynomials dynamically. To implement one layer of PNNs, the various types of simple polynomials are used so that PNNs have flexibility and versatility. Although the structural complexity of the implemented PNNs is high, the PNNs become a high order-multi input polynomial finally. To estimate the coefficients of a polynomial neuron, The weighted linear discriminant analysis. The output of fuzzy rule system with PNNs as the consequent part is the linear combination of the output of several PNNs. To evaluate the classification ability of the proposed pattern classifier, we make some experiments with several machine learning data sets.

신경망 최적화 회로에 의한 여유자유도를 갖는 로보트의 제어 (Redundant Robot Control by Neural Optimization Networks)

  • 현웅근;서일홍
    • 대한전기학회논문지
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    • 제39권6호
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    • pp.638-648
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    • 1990
  • An effective resolved motion control method of redundant manipulators is proposed to minimize the energy consumption and to increase the dexterity while satisfying the physical actuator constraints. The method employs the neural optimization networks, where the computation of Jacobian matrix is not required. Specifically, end effector movement resulting from each joint differential motion is first separated into orthogonal and tangential components with respect to a given desired trajectory. Then the resolved motion is obtained by neural optimization networks in such a way that 1) linear combination of the orthogonal components should be null 2) linear combination of the tangential components should be the differential length of the desired trajectory, 3) differential joint motion limit is not violated, and 4) weighted sum of the square of each differential joint motion is minimized. Here the weighting factors are controlled by a newly defined joint dexterity measure as the ratio of the tangential and orthogonal components.

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