• Title/Summary/Keyword: Cross-correlation analysis

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CMP cross-correlation analysis of multi-channel surface-wave data

  • Hayashi Koichi;Suzuki Haruhiko
    • Geophysics and Geophysical Exploration
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    • v.7 no.1
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    • pp.7-13
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    • 2004
  • In this paper, we demonstrate that Common Mid-Point (CMP) cross-correlation gathers of multi-channel and multi-shot surface waves give accurate phase-velocity curves, and enable us to reconstruct two-dimensional (2D) velocity structures with high resolution. Data acquisition for CMP cross-correlation analysis is similar to acquisition for a 2D seismic reflection survey. Data processing seems similar to Common Depth-Point (CDP) analysis of 2D seismic reflection survey data, but differs in that the cross-correlation of the original waveform is calculated before making CMP gathers. Data processing in CMP cross-correlation analysis consists of the following four steps: First, cross-correlations are calculated for every pair of traces in each shot gather. Second, correlation traces having a common mid-point are gathered, and those traces that have equal spacing are stacked in the time domain. The resultant cross-correlation gathers resemble shot gathers and are referred to as CMP cross-correlation gathers. Third, a multi-channel analysis is applied to the CMP cross-correlation gathers for calculating phase velocities of surface waves. Finally, a 2D S-wave velocity profile is reconstructed through non-linear least squares inversion. Analyses of waveform data from numerical modelling and field observations indicate that the new method could greatly improve the accuracy and resolution of subsurface S-velocity structure, compared with conventional surface-wave methods.

창원시 대산면 강변충적층의 지하수위, 하천수위, 강수량의 관련성 연구

  • 정재열;함세영;김형수;차용훈;장성
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2004.04a
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    • pp.447-450
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    • 2004
  • This study was conducted to characterize groundwater and river-water fluctuations at a riverbank filtration site in Daesan-myeon adjacent to the Nakdong River, using time series analysis. Water levels from six observation wells from January 2003 to October 2003 were measured. The autocorrelation analysis indicates that the wells are divided into three groups: group 1 represents strong linearity and memory, group 2 intermediate linearity and memory, and group 3 weak linearity and memory. The analysis indicates that groundwater levels in different monitoring wells vary in response to river-water levels, groundwater withdrawal and seasonal rainfall. Cross-correlation was also divided into three groups. Group 1 shows the highest cross-correlation function (0.49 - 0.54) for a lag time of 0 hours, group 2 intermediate cross-correlation function (0.34 - 0.45), and group 3 the lowest cross-correlation function (0.23 - 0.25). Different cross-correlation functions among the 3 groups are interpreted as an effect of tile distance from the river to the pumping wells.

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Estimation of high-dimensional sparse cross correlation matrix

  • Yin, Cao;Kwangok, Seo;Soohyun, Ahn;Johan, Lim
    • Communications for Statistical Applications and Methods
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    • v.29 no.6
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    • pp.655-664
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    • 2022
  • On the motivation by an integrative study of multi-omics data, we are interested in estimating the structure of the sparse cross correlation matrix of two high-dimensional random vectors. We rewrite the problem as a multiple testing problem and propose a new method to estimate the sparse structure of the cross correlation matrix. To do so, we test the correlation coefficients simultaneously and threshold the correlation coefficients by controlling FRD at a predetermined level α. Further, we apply the proposed method and an alternative adaptive thresholding procedure by Cai and Liu (2016) to the integrative analysis of the protein expression data (X) and the mRNA expression data (Y) in TCGA breast cancer cohort. By varying the FDR level α, we show that the new procedure is consistently more efficient in estimating the sparse structure of cross correlation matrix than the alternative one.

Computing Method of Cross-Correlation of Non-Linear Sequences Using Subfield (부분체를 이용한 비선형 수열의 상호상관관계의 효율적인 계산방법)

  • Choi, Un-Sook;Cho, Sung-Jin;Kim, Seok-Tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.8
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    • pp.1686-1692
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    • 2012
  • Spreading sequence play an important role in wireless communications, such as in a CDMA(code division multiple access) communication system and multi-carrier spectrum communication system. Spreading sequences with low cross-correlation, in a direct-sequence spread spectrum communication system, help to minimize multiple access interference and to increase security degree of system. Analysis of cross-correlations between the sequences is a necessary process to design sequences. However it require lots of computing time for analysis of cross-correlations between sequences. In this paper we propose a method which is possible to compute effectively cross-correlation using subfield in the process of practical computation of cross-correlation between nonlinear binary sequences.

In Vivo Quantitative Analysis of PKA Subunit Interaction and cAMP Level by Dual Color Fluorescence Cross Correlation Spectroscopy

  • Park, Hyungju;Pack, Changi;Kinjo, Masataka;Kaang, Bong-Kiun
    • Molecules and Cells
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    • v.26 no.1
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    • pp.87-92
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    • 2008
  • We employed dual color Fluorescence Cross Correlation Spectroscopy (FCCS) to measure the interaction between PKA regulatory (RII) and catalytic subunits (CAT) in living cells. Elevation of intracellular cAMP with forskolin decreased the cross-correlation amplitude between RFP-fused RII (RII -mRFP) and GFP-fused CAT (CAT-EGFP) by 50%, indicating that cAMP elevation leads to dissociation of RII-CAT complexes. Moreover, diffusion coefficient analysis showed that the diffusion rate of CAT-EGFP was significantly increased, suggesting that the decreased RII-CAT association caused by cAMP generated free CAT subunits. Our study demonstrates that in vivo FCCS measurements and their quantitative analysis permit one not only to directly quantify protein-protein interactions but also to estimate changes in the intracellular cAMP concentration.

Development of Fast and Exact FFT Algorithm for Cross-Correlation PIV (상호상관 PIV기법을 위한 빠르고 정확한 FFT 알고리듬의 개발)

  • Yu, Kwon-Kyu;Kim, Dong-Su;Yoon, Byung-Man
    • Journal of Korea Water Resources Association
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    • v.38 no.10 s.159
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    • pp.851-859
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    • 2005
  • Normalized cross-correlation (correlation coefficient) is a useful measure for pattern matching in PIV (Particle Image Velocimetry) analysis. Because it does not have a corresponding simple expression in frequency domain, several fast but inexact measures have been used. Among them, three measures of correlation for PIV analysis and the normalized cross-correlation were evaluated with a sample calculation. The test revealed that all other proposed correlation measures sometimes show inaccurate results, except the normalized cross-correlation. However, correlation coefficient method has a weakpoint that it requires so long time for calculation. To overcome this shortcoming, a fast and exact method for calculating normalized cross-correlation is suggested. It adopts Fast Fourier Transform (FFT) for calculation of covariance and the successive-summing method for the denominator of correlation coefficient. The new algorithm showed that it is really fast and exact in calculating correlation coefficient.

Terrain reference navigation algorithm based on cross-correlation matching using topography characteristics (지형의 특성을 이용한 상호상관정합 기반 지형참조항법 알고리즘)

  • Lee, Bo-Mi;Kwon, Jay-Hyoun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2010.04a
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    • pp.161-164
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    • 2010
  • The study on terrain referenced navigation has been proceeded from 1940s in advanced country with the object of military. In this study, the analysis regarding algorithm developed using cross-correlation matching algorithm and extended Kalman filter and simulation will be introduced. As a result, the standard deviation of position error from cross-correlation matching algorithm has been calculated 34.3m. It meant that the result has stable accuracy on the navigation. However, further study on terrain referenced navigation based on analysis of various topographic characteristics should be performed.

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ANALYSIS OF THE SEQUENCES WITH OPTIMAL CROSS-CORRELATION PROPERTY

  • Kwon, Min-Jeong;Cho, Sung-Jin
    • Journal of applied mathematics & informatics
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    • v.31 no.5_6
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    • pp.869-876
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    • 2013
  • The design of large family size with the optimal cross-correlation property is important in spread spectrum and code division multiple access communication systems. In this paper we present the sequences with the decimation $d=2{\cdot}2^m-1$, calculate the cross-correlation spectrum for $0{\leq}t{\leq}2^n-2$ and count the number of the value $2^m-1$ occurring for $0{\leq}{\tau}2^n-2$. The sequences have the optimal cross-correlation property. The work on this paper can make it easier to count the number of the whole value occurring for $0{\leq}{\tau}2^n-2$.

Design of customized product recommendation model on correlation analysis when using electronic commerce (전자상거래 이용시 연관성 분석을 통한 맞춤형 상품추천 모델 설계)

  • Yang, MingFei;Park, Kiyong;Choi, Sang-Hyun
    • Journal of the Korea Convergence Society
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    • v.13 no.3
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    • pp.203-216
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    • 2022
  • In the recent business environment, purchase patterns are changing around the influence of COVID-19 and the online market. This study analyzed cluster and correlation analysis based on purchase and product information. The cluster analysis of new methods was attempted by creating customer, product, and cross-bonding clusters. The cross-bonding cluster analysis was performed based on the results of each cluster analysis. As a result of the correlation analysis, it was analyzed that more association rules were derived from a cross-bonding cluster, and the overlap rate was less. The cross-bonding cluster was found to be highly efficient. The cross-bonding cluster is the most suitable model for recommending products according to customer needs. The cross-bonding cluster model can save time and provide useful information to consumers. It is expected to bring positive effects such as increasing sales for the company.

Improved Correlation Identification of Subsurface Using All Phase FFT Algorithm

  • Zhang, Qiaodan;Hao, Kaixue;Li, Mei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.495-513
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    • 2020
  • The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.