• Title/Summary/Keyword: Correlation Method

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Detection and Location of Cable Fault Using Improved SSTDR (개선된 SSTDR을 이용한 케이블 고장 검출과 위치 계산)

  • Jeon, Jeong-Chay;Kim, Jae-Jin;Choi, Myeong-Il
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.9
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    • pp.1583-1589
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    • 2016
  • This paper proposes an improved spread spectrum time domain reflectometry (ISSTDR) using time-frequency correlation and reference signal elimination method in order to have more accurate fault determination and location detection than conventional (SSTDR) despite increased signal attenuation due to the long distance to cable fault location. The proposed method has a two-step process: the first step is to detect a peak location of the reference signal using time-frequency correlation analysis, and the second step is to detect a peak location of the correlation coefficient of the reflected signal by removing the reference signal. The proposed method was validated through comparison with existing SSTDR methods in open-and short-circuit fault detection experiments of low voltage power cables. The experimental results showed that the proposed method can detect correlation coefficients at fault locations accurately despite reflected signal attenuation so that cable faults can be detected more accurately and clearly in comparison to existing methods.

Noisy Band Removal Using Band Correlation in Hyperspectral lmages

  • Huan, Nguyen Van;Kim, Hak-Il
    • Korean Journal of Remote Sensing
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    • v.25 no.3
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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.

Pseudo-Correlation-Function Based Unambiguous Tracking Technique for CBOC (6,1,1/11) Signals

  • Jeong, Gil-Seop;Kong, Seung-Hyun
    • Journal of Positioning, Navigation, and Timing
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    • v.4 no.3
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    • pp.107-114
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    • 2015
  • Binary Offset Carrier (BOC) signal planned for future Global Navigation Satellite System (GNSS) provided better positioning accuracy and smaller multipath error than GPS C/A signal. However, due to the multiple side peaks in the auto-correlation function (ACF) of the BOC modulated signals, a receiver may false lock onto one of the side peaks in the tracking mode. This false lock would then result in a fatal tracking error. In this paper, we propose an unambiguous tracking method for composite BOC (CBOC) signals to mitigate this problem. It aims to reduce the side peaks of the ACF of CBOC modulated signals. It is based on the combination of traditional CBOC correlation function (CF) and reference CF of unmodulated pseudo- random noise code (PRN code). First, we present that cross-correlation function (CCF) with unmodulated PRN code is close to the secondary peaks of the traditional CBOC. Then, we obtain an unambiguous correlation function by subtracting traditional CBOC ACF from these CFs. Finally, the tracking performance for the CBOC signals is examined, and it is shown that the proposed method has better performance than the traditional unambiguous tracking method in additive white Gaussian noise (AWGN) channel.

Latin Hypercube Sampling Based Probabilistic Small Signal Stability Analysis Considering Load Correlation

  • Zuo, Jian;Li, Yinhong;Cai, Defu;Shi, Dongyuan
    • Journal of Electrical Engineering and Technology
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    • v.9 no.6
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    • pp.1832-1842
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    • 2014
  • A novel probabilistic small signal stability analysis (PSSSA) method considering load correlation is proposed in this paper. The superiority Latin hypercube sampling (LHS) technique combined with Monte Carlo simulation (MCS) is utilized to investigate the probabilistic small signal stability of power system in presence of load correlation. LHS helps to reduce the sampling size, meanwhile guarantees the accuracy and robustness of the solutions. The correlation coefficient matrix is adopted to represent the correlations between loads. Simulation results of the two-area, four-machine system prove that the proposed method is an efficient and robust sampling method. Simulation results of the 16-machine, 68-bus test system indicate that load correlation has a significant impact on the probabilistic analysis result of the critical oscillation mode under a certain degree of load uncertainty.

A Study on the Maximizing Coverage for Recommender System

  • Lee, Hee-Choon;Lee, Seok-Jun;Park, Ji-Won;Kim, Chul-Seoung
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.11a
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    • pp.119-128
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    • 2006
  • The similarity weight, the pearson's correlation coefficient, which is used in the recommender system has a weak point that it cannot predict all of the prediction value. The similarity weight, the vector similarity, has a weak point of the high MAE although the prediction coverage using the vector similarity is higher than that using the pearson's correlation coefficient. The purpose of this study is to suggest how to raise the prediction coverage. Also, the MAE using the suggested method in this study was compared both with the MAE using the pearson's correlation coefficient and with the MAE using the vector similarity, so was the prediction coverage. As a result, it was found that the low of the MAE in the case of using the suggested method was higher than that using the pearson's correlation coefficient. However, it was also shown that it was lower than that using the vector similarity In terms of the prediction coverage, when the suggested method was compared with two similarity weights as I mentioned above, it was found that its prediction coverage was higher than that pearson's correlation coefficient as well as vector similarity.

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Blind OFDM Synchronization Algorithm using Cyclic Correlation (순환상관(Cyclic Correlation)을 이용한 OFDM 시스템에서의 블라인드 동기 알고리즘)

  • Park Byungjoon;Ko Eunseok;Kang Changeon;Hong Daesik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.1C
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    • pp.92-98
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    • 2005
  • In this paper, blind synchronization algorithm is developed for estimating jointly timing and frequency offset of OFDM system. The proposed estimator exploits the second-order cyclostationarity of received signals, and then uses the information of symbol timing and carrier frequency offset appeared in the cyclic correlation. As a bling estimator, the information of impulse response of channel and training symbols are not required. The performance of the proposed method is consistent in spite of channel conditions in mean squre error sense, and simulation results prove it. For more accurate estimaion, the method that averages cyclic correlation is applied. In this case, the performance of averaging method is better.

CASE INFLUENCE ON MULTIPLE CORRELATION COEFFICIENT

  • KIM, Myung-Geun
    • Journal of applied mathematics & informatics
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    • v.19 no.1_2
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    • pp.521-525
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    • 2005
  • Case deletion diagnostic for multiple correlation coefficient is considered. A method of detecting observations that can hide or create multicollinearity is suggested. A numerical example is given for illustration.

A Hand Gesture Recognition Method using Inertial Sensor for Rapid Operation on Embedded Device

  • Lee, Sangyub;Lee, Jaekyu;Cho, Hyeonjoong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.757-770
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    • 2020
  • We propose a hand gesture recognition method that is compatible with a head-up display (HUD) including small processing resource. For fast link adaptation with HUD, it is necessary to rapidly process gesture recognition and send the minimum amount of driver hand gesture data from the wearable device. Therefore, we use a method that recognizes each hand gesture with an inertial measurement unit (IMU) sensor based on revised correlation matching. The method of gesture recognition is executed by calculating the correlation between every axis of the acquired data set. By classifying pre-defined gesture values and actions, the proposed method enables rapid recognition. Furthermore, we evaluate the performance of the algorithm, which can be implanted within wearable bands, requiring a minimal process load. The experimental results evaluated the feasibility and effectiveness of our decomposed correlation matching method. Furthermore, we tested the proposed algorithm to confirm the effectiveness of the system using pre-defined gestures of specific motions with a wearable platform device. The experimental results validated the feasibility and effectiveness of the proposed hand gesture recognition system. Despite being based on a very simple concept, the proposed algorithm showed good performance in recognition accuracy.

Detection and Recovery of Occluded Face Images Based on Correlation (상관관계에 기반한 가려진 얼굴 영상 검출 및 복원)

  • Lee, Ji-Eun;Kwak, No-Jun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.5
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    • pp.72-83
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    • 2011
  • In this paper, we propose a method to detect and recover the occluded parts of face images using the correlation between pairs of pixels. In a training stage, correlation coefficients between every pairs of pixels are calculated using the occlusion-free face images. Once a new occluded face image is shown, the occluded area is detected and recovered using the correlation coefficients obtained in the training stage. We compare the performance of the proposed method with the conventional method based on PCA. The results show that the proposed method detects and recovers occluded area with much smaller noises than the conventional PCA based method. Moreover, recovered images by the proposed method were more smooth with reduced blurring effect.

Text Verification Based on Sub-Image Matching (부분 영상 매칭에 기반한 텍스트 검증)

  • Son Hwa Jeong;Jeong Seon Hwa;Kim Soo Hyung
    • The KIPS Transactions:PartB
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    • v.12B no.2 s.98
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    • pp.115-122
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    • 2005
  • The sub-mage matching problem in which one image contains some part of the other image, has been mostly investigated on natural images. In this paper, we propose two sub-image matching techniques: mesh-based method and correlation-based method, that are efficiently used to match text images. Mesh-based method consists of two stages, box alignment and similarity measurement by extracting the mesh feature from the two images. Correlation-based method determines the similarity using the correlation of the two images based on FFT function. We have applied the two methods to the text verification in a postal automation system and observed that the accuracy of correlation-based method is $92.7\%$ while that of mesh-based method is $90.1\%$.