• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.279-284
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• 2017

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative time delay between two or more received signals for the direct signal must be determined. Although the GCC (Generalized Cross-Correlation) method is the most popular technique, an approach based on CCA (Canonical Correlation Analysis) was also proposed for the TDE (Time Delay Estimation). In this paper, we propose a new adaptive algorithm based on CCA in order to utilized the sparsity in the eigenvector of CCA based time delay estimator. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue with log-sum regularization in order to utilize the sparsity in the eigenvector. We have performed simulations for several SNR(signal to noise ratio)s, showing that the new CCA based algorithm can estimate the time delays more accurately than the conventional CCA and GCC based TDE algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.12-20
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• 1993

In a conventional adaptive echo canceller, an ADF(Adaptive Digital Filter) with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to compute the coefficients, and NET detector using energy comparison method prevents the ADF to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yields more accurate detection of the start point of the NET signal.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.23-28
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• 1992

The purpose of this paper is to develop a new adaptive echo canceller improving convergence speed and near-end-talker detection performance of the conventional echo canceller. In a conventional adaptive echo canceller, an adaptive digital filter with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to cote the coefficients, and NET detector using energy comparison method prevents the adaptive digital filter to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF(Adaptive Digital Filter) output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yield more accurate detection of the start point of the NET signal.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.323-327
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• 2007

In this paper, objectively quantified consonance of complex sound is proposed as a new psychoacoustical parameter. Proposing algorithm quantifies consonance of complex sound after applying psycho acoustical models which are parts of human perception such as masking effect, equal loudness contour, and critical band. To verify proposing algorithm, experiments with 10 car horn signals which have different complex sound were performed. The experiments show cross correlation of 0.95 between objectively quantified consonance by proposing algorithm and subjectively assessed consonance by listening tests. Considering the fact that there are few psychoacoustical parameter except Zwicker parameter, proposing algorithm will help to quantify psychoacoustical effect of complex sounds objectively.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.1
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• pp.127-134
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• 2016

Most of reconstruction algorithms for the calculation of temperature distributions in CT (computed tomography)-TDLAS (tunable diode laser absorption spectroscopy) are based upon two-line thermometry method. This method gives unstable calculation convergence due to signal noise, bias error, and signal mis-matches. In this study, a new reconstruction algorithm based on cross-correlation for temperature calculation is proposed. The patterns of the optical signals at all wave lengths were used to reconstruct the temperature distribution. Numerical test has been made using phantom temperature distributions. Using these phantom temperature data, absorption spectra for all wave lengths were constructed, and these spectra were regarded as the signals that would be obtained in an actual experiments. Using these virtually generated experimental signals, temperature distribution was once again reconstructed, and was compared with those of the original phantom data. Calculation errors obtained by the newly proposed algorithm were slightly large at high temperatures with small errors at low temperature.

• Korean Management Science Review
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• v.23 no.1
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• pp.63-74
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• 2006

Decision tree induction algorithm is one of the most widely used methods in classification problems. However, they could be trapped into a local minimum and have no reasonable means to escape from it if tree algorithm uses top-down search algorithm. Further, if irrelevant or redundant features are included in the data set, tree algorithms produces trees that are less accurate than those from the data set with only relevant features. We propose a hybrid algorithm to generate decision tree that uses genetic programming with sequentially selected features. Correlation-based Feature Selection (CFS) method is adopted to find relevant features which are fed to genetic programming sequentially to find optimal trees at each iteration. The new proposed algorithm produce simpler and more understandable decision trees as compared with other decision trees and it is also effective in producing similar or better trees with relatively smaller set of features in the view of cross-validation accuracy.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.345-352
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• 2017

We propose a methods which is reducing direction estimation error of sound source in the reverberant and noisy environments. The proposed algorithm divides speech signal into voice and unvoice using VAD. We estimate the direction of source when current frame is voiced. TDOA (Time-Difference of Arrival) between microphone array using the GCC-PHAT (Generalized Cross Correlation with Phase Transform) method will be estimated in that frame. Then, we compare the peak value of cross-correlation of two signals applied to estimated time-delay with other time-delay in time-table in order to improve the accuracy of source location. If the angle of current frame is far different from before and after frame in successive voiced frame, the angle of current frame is replaced with mean value of the estimated angle in before and after frames.

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

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.985-990
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• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300m.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.798-803
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• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband sound from a leak location and this sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300m.