• Proceedings of the KOSOMBE Conference
• /
• v.1990 no.11
• /
• pp.99-102
• /
• 1990

Cross correlation method was newly applied for the calculation of latency of evoked otoacoustic emission. The latency was calculated from the main peak of cross correlation function, which is one of possible definition of latency. The output was also compared with those of conventional autocorrelation method. The results show that cross correlation method has better performance than that of conventional method.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2010.04a
• /
• pp.161-164
• /
• 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.

• Journal of Information Technology Applications and Management
• /
• v.24 no.1
• /
• pp.157-167
• /
• 2017

This paper proposes a simple sound source localization (SSL) method based on signal energies comparison and partial cross correlation for TDOA computation. Many sound source localization methods include multiple TDOA computations in order to eliminate front-back confusion. Multiple TDOA computations however increase the methods' computation times which need to be as minimal as possible for real-time applications. Our aim in this paper is to achieve the same results of localization using fewer computations. Using three microphones, we first compare signal energies to predict which quadrant the sound source is in, and then we use partial cross correlation to estimate the TDOA value before computing the azimuth value. Also, we apply a threshold value to reinforce our prediction method. Our experimental results show that the proposed method has less computation time; spending approximately 30% less time than previous three microphone methods.

• Molecules and Cells
• /
• v.26 no.1
• /
• pp.87-92
• /
• 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.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06a
• /
• pp.781-784
• /
• 1994

Detecting partial discharge(PD) and locating its source are one of many diagnosis methods. Location the PD source is very important to reduce the time and cost of repairing power transformers. And to locate the PD source, the cross-correlation method is a well known one. But there many spurious peaks in cross-correlation, and occasionally, some peaks could be bigger than the true one. In order to analysis these spurious peaks and to reduce them, we have done many experiments and simulations. As the results we could reduce the spurious peaks, and get well defined cross-correlation from which it is easy to locate the PD source accurately.

• Smart Structures and Systems
• /
• v.16 no.1
• /
• pp.213-222
• /
• 2015

Early detection and precise location of leakage is of great importance for life-cycle maintenance and management of municipal pipeline system. In the past few years, acoustic emission (AE) techniques have demonstrated to be an excellent tool for on-line leakage detection. Regarding the multi-mode and frequency dispersion characteristics of AE signals propagating along a pipeline, the direct cross-correlation technique that assumes the constant AE propagation velocity does not perform well in practice for acoustic leak location. This paper presents an improved cross-correlation method based on wavelet transform, with due consideration of the frequency dispersion characteristics of AE wave and the contribution of different mode. Laboratory experiments conducted to simulate pipeline gas leakage and investigate the frequency spectrum signatures of AE leak signals. By comparing with the other methods for leak location identification, the feasibility and superiority of the proposed method are verified.

• Proceedings of the KOSOMBE Conference
• /
• v.1991 no.05
• /
• pp.9-12
• /
• 1991

The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

• Journal of the Korean Society of Radiology
• /
• v.7 no.5
• /
• pp.347-352
• /
• 2013

In this study, we analyze the cross correlation between Gamma exposure rates and Rainfall, Hours of daylight, Average wind speed using cross-correlation coefficient ${\rho}_{DCCA}$ and DCCA cross-correlation coefficient(DCCA ${\rho}$) method. Our data are measured simultaneous in Gangneung regional. First, we find the ${\rho}_{DCCA}$ between Gamma exposure rates and Rainfall is Day(3~7days) 0.57~0.48, Month(30days) 0.39, Season(90days) 0.34, Year(360days) 0.26, between Gamma exposure rates and Hours of daylight is Day -0.20~-0.23, Month -0.22, Season -0.17, Year -0.13, between Gamma exposure rates and Average wind speed is Day -0.10~-0.12, Month -0.11, Season -0.05, Year -0.05. Second, our finding is cross- correlation between Gamma exposure rates and Rainfall, is no cross-correlation between Gamma exposure rates and Hours of daylight, Average wind speed.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.46 no.3
• /
• pp.244-250
• /
• 2018

Multilateration acquires the transponder signal of target from receivers installed on the ground and calculates the position of the target using the difference of the signal acquisition time of each receiver. One of the factors that influence the positioning accuracy of Multilateration using the TDOA calculation method is the error due to the precision measurement of signal input time. When measuring the signal input time at the receiver, the input signal is sampled using the reference clock of the receiver and a reference sample having the same sampling rate is applied to the cross correlation technique. Therefore, the accuracy of the signal input time is proportional to the reference clock. In this paper, the algorithm for precisely measuring the signal input time by performing cross correlation between the input signal of the receiver and DRS(Delayed Reference Sample) is proposed. In order to verify this, we implemented the pulse signal of the transponder that is transmitted from the target using Matlab. Through the simulation, cross correlation between the proposed DRS and the input signal was performed. From this result, the performance of the precise measurement of signal input time was analyzed.

• The Journal of the Acoustical Society of Korea
• /
• v.37 no.5
• /
• pp.271-275
• /
• 2018

There are several methods for estimating the time delay between incoming signals to two sensors. Among them, the GCC-PHAT (Generalized Cross Correlation-Phase Transform) method, which estimates the relative delay from the signal whitening and the cross-correlation between the different signal inputs to the two sensors, is a traditionally well known method for achieving stable performance. In this paper, we have identified a part of GCC-PHAT that can improve the periodicity. Also, we apply the auto-correlation method that is widely used as a method to improve the periodicity. Comparing the proposed method with the GCC-PHAT method, we show that the proposed method improves the mean square error performance by 5 dB ~ 15 dB at the SNR above 0 dB for white Gaussian signal source and also show that the method improves the mean square error performance up to 15 dB at the SNR above 2 dB for the color signal source.