• 제목/요약/키워드: Correlation Coefficient Method

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일반적인 센서잡음상관에 이용되는 도래방향각 예측 방법 (A Direction Finding Method for General Sensor Noise Correlation)

  • 이일근
    • 한국통신학회논문지
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    • 제17권4호
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    • pp.379-386
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    • 1992
  • In this paper a direction finding method which can which can estimate the direction angles of source signals impinging on the sensor array in which sensor noises are correlated is studied. This method performs the estimation of source direction angles form sensors, regardless of sensor noise correlation, by eliminating the sensor noise correlation coefficient which can be accurately estimated. Finally, this paper shows, through the computer simulation, that the proposed, method is extremely useful and superior when there exists the noise correlation between sensors, .

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DCCA 방법으로 연결된 한반도의 기온 네트워크 분석 (Temperature network analysis of the Korean peninsula linking by DCCA methodology)

  • 민승식
    • 응용통계연구
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    • 제29권7호
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    • pp.1445-1458
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    • 2016
  • 본 논문에서는 1976년부터 2015년까지 40년 간, 59개 지역 기온 시계열을 대상으로 degrended cross-correlation analysis(DCCA) 방법을 이용한 상관 계수를 도출하였다. 4년 단위의 평균기온, 최고기온, 최저기온 시계열을 분석하여 상관계수 값이 0.9 이상이면 단위 기간 동안 두 지역의 온도 상관성이 존재하는 것으로 판단하고, 두 지역 간의 연결선을 만드는 방식으로 네트워크를 구축하였다. 이후 네트워크 이론을 바탕으로 평균 경로 길이, 결집 계수, 유사성, 모듈성 등의 값들을 도출하였다. 그 결과, 기온 네트워크는 좁은 세상 성질을 만족하고, 유사성과 모듈성이 높은 네트워크임을 알 수 있었다.

지능형 휠체어 적용을 위한 기울기 히스토그램의 상관계수를 이용한 도로위의 이륜차 인식 (Two Wheeler Recognition Using the Correlation Coefficient for Histogram of Oriented Gradients to Apply Intelligent Wheelchair)

  • 김범국;박상희;이영학;이강화
    • 대한의용생체공학회:의공학회지
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    • 제32권4호
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    • pp.336-344
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    • 2011
  • This article describes a new recognition algorithm using correlation coefficient for intelligent wheelchair to avoid collision for elderly or disabled people. The correlation coefficient can be used to represent the relationship of two different areas. The algorithm has three steps: Firstly, we extract an edge vector using the Histogram of Oriented Gradients(HOG) which includes gradient information and unique magnitude for each cell. From this result, the correlation coefficients are calculated between one cell and others. Secondly, correlation coefficients are used as the weighting factors for normalizing the HOG cell. And finally, these features are used to classify or detect variable and complicated shapes of two wheelers using Adaboost algorithm. In this paper, we propose a new feature vectors which is calculated by weighted cell unit to classify with multiple view-based shapes: frontal, rear and side views($60^{\circ}$, $90^{\circ}$ and mixed angle). Our experimental results show that two wheeler detection system based on a proposed approach leads to a higher detection accuracy than the method using traditional features in a similar detection time.

THE DEVELOPMENT OF THE WATER LOADED PRESSURE METHOD FOR MEASURING EGGSHELL QUALITY

  • Kang, C.W.;Nam, K.T.;Olson, O.E.;Carlson, C.W.
    • Asian-Australasian Journal of Animal Sciences
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    • 제9권6호
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    • pp.723-726
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    • 1996
  • A water loaded pressure device using water as the breaking force was developed to evaluate eggshell strength and compared with a dropping ball techniques. Further, relationships of shell thickness and weight of eggs to shell strength were also studied. Values for both of the shell strength measuring methods showed a highly significant correlation (p < 0.001) with shell thickness. The water loaded pressure method had a much higher simple correlation coefficient for shell thickness (r = + 0.786) than the dropping ball method (r = + 0.577). The shell strength measured by the water loaded pressure method appeared not to be correlated to egg weight. On the other hand, the negative sign of the standard partial regression coefficient and the partial regression coefficient of egg weight in the estimated multiple regression equation implied that for a given shell thickness a larger egg tended to have less shell strength than a smaller egg.

CORRELATION COEFFICIENT OF GENERALIZED INTUITIONISTIC FUZZY SETS BY STATISTICAL METHOD

  • PARK, JIN HAN;PARK, YONG BEOM;LIM, KI MOON
    • 호남수학학술지
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    • 제28권3호
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    • pp.317-326
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    • 2006
  • Based on the geometrical representation of a generalized intuitionistic fuzzy set, we take into account all three parameters describing generalized intuitionistic fuzzy set and propose new methods to calculate the correlation coefficient for generalized intuitionistic fuzzy sets by means of mathematical statistics.

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해수면 온도분포에 대한 최대상관계수법과 역행렬법의 적용 (Application of MCC and Inverse Method for the AVHRR/SST)

  • 이태신;정종률
    • 대한원격탐사학회지
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    • 제11권1호
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    • pp.19-29
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    • 1995
  • The surface velocities were estimated by the Maximum Cross Correlation(MCC) method and an inverse method from AVHRR/SST. In the results of MCC, discontinuous flow fields were estimated in the case that cross correlation coefficient was above 0.5 but these flow pattern disappeared when cross correlation coefficient was above 0.9. This estimation was conspicuous near SST patterns of eddies. In the results of inverse method, flow field was continuous and eddy motion was estimated definitely but the velocity was overstimated in compared with MCC result over the area of small temperature gradient. This result may be due to temperature error included in SST calculated and spatial variation of heat flux.

여자대학생의 체형과 의복의 원형구조법에 관한 연구 -신분각부위의 상관 계수를 중심으로- (A Study on the pattern construction and body structure of Korean college girls on the basis of correlation coefficient of each body part.)

  • 임원자
    • 대한가정학회지
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    • 제8권1호
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    • pp.21-35
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    • 1970
  • 1. For the purpose of making the basic pattern construction 100 girls attending the Seoul National University College of Home Economics were measured in finding of body size and coefficient of correlation which would be used as one basis of this study. 2. Coefficient of correlation of each body part based on the breast width was shown as follows; Correlation coefficients of bust to waist and hip were high and those of bust to shoulder width, neck height, back width, and breast width were low. None of that was found between bust and back length. It was not recognized so scientific to adjust the basic pattern construction with figures proportioned by those of neck, shoulder width, breast width, and back width. 3. The method of basic pattern construction obtained by this research has been demonstrated in direct wearing since 1967. It is believed that the result will contribute a great benefit in teaching clothing as well as in mass production industry of ready-made garments.

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Noisy Band Removal Using Band Correlation in Hyperspectral lmages

  • Huan, Nguyen Van;Kim, Hak-Il
    • 대한원격탐사학회지
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    • 제25권3호
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    • pp.263-270
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    • 2009
  • Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

통계적 분석기법을 이용한 디젤기관의 고장진단 방법에 관한 연구 (The Fault Diagnosis Method of Diesel Engines Using a Statistical Analysis Method)

  • 김영일;오현경;유영호
    • Journal of Advanced Marine Engineering and Technology
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    • 제30권2호
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    • pp.247-252
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    • 2006
  • Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn until signal is growing to abnormal state that the signal is over or under the set point. therefore cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without any additional sensors. By analyzing the data with high correlation coefficient(CC), correlation level of interactive data can be defined. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC. FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

통계적분석기법을 이용한 디젤기관의 고장진단 방법에 관한 연구 (The Fault Diagnosis Method of Diesel Engines Using a Statistical Analysis Method)

  • 김영일;오현경;천행춘;유영호
    • 한국마린엔지니어링학회:학술대회논문집
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    • 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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    • pp.281-286
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    • 2005
  • Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn while signal is growing to abnormal state until the signal is over or under the set point and cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. By analyzing this data having high correlation coefficient(CC), correlation level of interactive data can be understood. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC, FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

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