• Journal of Biomedical Engineering Research
• /
• v.12 no.1
• /
• pp.19-22
• /
• 1991

Cross correlation method was newly applied for the calculation of latency of evoked otoacoustic emission. The latency was calculated froth 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.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.12
• /
• pp.2324-2328
• /
• 2010

In this paper we proposed a new algorithm that can reduce the open-loop pitch estimation time of G.723.1. The time domain cross-correlation method is simple but has long processing time by recursive multiplication. For reduction of processing time, we use the method that compute the cross-correlation by multiplying the Fourier value of speech by it's complex conjugate. Also, we can reduce the processing time by omitting the bit-reversing of FFT and IFFT for time-frequency domain transform. As a result, the processing time of improved hybrid domain cross-correlation algorithm is reduced by 67.37% of conventional time domain cross-correlation.

• Nuclear Engineering and Technology
• /
• v.44 no.8
• /
• pp.977-984
• /
• 2012

The cross-correlation technique has been widely used for leakage detection of buried pipes, and this technique can be successfully applied when the leakage signal has a high signal-to-noise ratio. In the case of a power plant, the measured leakage signals obtained from the sensors may contain background noise and mechanical noise generated by adjacent machinery. In such a case, the conventional method using the cross-correlation function may fail to estimate the leakage point. In order to enhance the leakage estimation capability of a buried pipe in a noisy environment, an improved cross-correlation technique is proposed. It uses a noise rejection technique in the frequency domain to effectively eliminate the tonal noise due to rotating machinery. Experiments were carried out to verify the validity of the proposed method. The results show that even in a tonal noisy environment, the proposed method can provide more reliable means for estimating the time delay of the leakage signals.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.2
• /
• pp.495-513
• /
• 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.

• Geophysics and Geophysical Exploration
• /
• v.7 no.1
• /
• pp.7-13
• /
• 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.

• 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 Korea Water Resources Association
• /
• v.38 no.10 s.159
• /
• pp.851-859
• /
• 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.

• 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.

• 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.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.43 no.10 s.352
• /
• pp.18-26
• /
• 2006

In this paper, we propose new beamforming algorithm which overcomes signal cancellation effect even high cross correlation existing between target and interfering signal. Using the proposed method, we show that direction of arrival (DOA) of interfering signal can be estimated using correlation matrix and the cross-correlation can be eliminated in the correlation matrix of input signal. The proposed method gives high performance enhancement compared with the spatial averaging method in our computer simulation results.