• The Journal of the Acoustical Society of Korea
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• v.25 no.4E
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• pp.142-147
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• 2006

Blind signal separation is known as a powerful tool for enhancing noisy speech in many real world environments. In this paper, it is demonstrated that the performance of blind signal separation can be further improved by combining with a null beamformer (NBF). Cascading the blind source separation with null beamforming is equivalent to the decomposition of the received signals into the direct parts and reverberant parts. Investigation of beam patterns of the null beamformer and blind signal separation reveals that directional null of NBF reduces mainly direct parts of the unwanted signals whereas blind signal separation reduces reverberant parts. Further, it is shown that the decomposition of received signals can be exploited to solve the local stability problem. Therefore, faster and improved separation can be obtained by removing the direct parts first by null beamforming. Simulation results using real office recordings confirm the expectation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.43-50
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• 2016

This paper is on an acoustic echo canceller solving the double-talk problem by using the blind signal separation technology. The acoustic echo canceller may be deteriorated or diverged during the double-talk period. So we use the blind signal separation to detect the double talking by separating the near-end speech signal from the mixed microphone signal. The blind signal separation extracts the near-end signal from dual microphones by the iterative computations using the 2nd order statistical character in the closed reverberation environment. By this method, the acoustic echo canceller operates irrespective of the double-talking. We verified performances of the proposed acoustic echo canceller in the computer simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods well, and then operates stably without diverging of the coefficients after ending the double-talking. The merits are in the simplicity and stability.

• ETRI Journal
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• v.45 no.1
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• pp.138-149
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• 2023

In this study, the problem of blind signal separation for coprime planar arrays is investigated. For coprime planar arrays comprising two uniform rectangular subarrays, we link the signal separation to the tensor-based model called coupled canonical polyadic decomposition (CPD) and propose an improved coupled trilinear decomposition approach. The output data of coprime planar arrays are modeled as a coupled tensor set that can be further interpreted as a coupled CPD model, allowing a signal separation to be achieved using coupled trilinear alternating least squares (TALS). Furthermore, in the procedure of the coupled TALS, a Vandermonde structure enforcing approach is explicitly applied, which is shown to ensure fast convergence. The results of Monto Carlo simulations show that our proposed algorithm has the same separation accuracy as the basic coupled TALS but with a faster convergence speed.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.319-326
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• 1996

Clinical myography(EMG) is a technique for diagnosing neuromuscular disorders by analyzing the electrical signal that can be records by needle electrode during a muscular contraction. The EMG signal arises from electrical discharges that accompany the generation of force by groups of muscular fiber, and the analysis of EMG signal provides symptoms that can distinguish disorder of mLecle from disor- ders of nerve. One of the methods for analysis of EMG signal is to separate the individual discharge-the motor unit action potentials(MVAPS) - from EMG signal. But we can only observe the EMG signal that is a superimposed version of time delayed MUAPS. To obtain the information about MUAP(, i.e., position, firing number, magnitude etc), first of all, a method that can separate each MUAP from the EMG signal must be developed Although the methods for MUAP separation have been proposed by many researcherl they have required heavy computational burden. In this paper, we proposed a new method that has less computational burden and performs more reliable separation of superimposed EMG signal using wavelet filter which has multiresolution analysis as major property. As a result, we develope the separation algorithm of superimposed EMG signal which has less computational burden than any other researchers and exacutes exact separation process. The performance of this method has been discussed in the automatic resolving procedure which is neccessary to identify every firing of every motor unit from the EMG pattern.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.131-138
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• 2014

This paper is on a stereo acoustic echo canceller with the blind signal separation for post processing. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals which are update signals of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals after the echo cancellers. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 2dB higher ERLE with the BSS post processing method than without this method. This stereo echo canceller showed the best performance in the case of inputting the real voice signal.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.125-131
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• 2012

This paper is on a stereo acoustic echo canceller with the blind signal separation. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals in the update signal of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 3dB higher ERLE in the case of using the BSS algorithm than the case of not using the BSS algorithm. But this echo canceller didn't get good performances in the case of inputting the white noises as stereo signals.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.237-245
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• 2012

This paper describes an acoustic echo canceller with double-talk by the blind signal separation. The acoustic echo canceller is deteriorated or diverged in the double-talk period. So we use the blind signal separation to estimate the near-end speech signal and to eliminate the estimated signal from the residual signal. The blind signal separation extracts the near-end signal with dual microphones by the iterative computations using the 2nd order statistical character. Because the mixture model of blind signal separation is multi-channel in the closed reverberation environment, we used the copied coefficients of echo canceller without computing the separation coefficients. By this method, the acoustic echo canceller operates irrespective of double-talking. We verified performances of the proposed acoustic echo canceller by simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods thoroughly, and then operates stably in the normal state without the divergence of coefficients after ending the double-talking. And it shows the ERLE of averagely 20dB higher than the normal LMS algorithm.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.25-28
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• 2003

The aim of this paper is to analyze the pathological voice by separating signal into periodic and aperiodic part. Separation was peformed recursively from the residual signal of voice signal. Based on initial estimation of aperiodic part of spectrum, aperiodic part is decided from the extrapolation method. Periodic part is decided by subtracting aperiodic part from the original spectrum. A parameter HNR is derived based on the separation. Parameter value statistics are compared with those of Jitter and Shimmer for normal, benign and malignant cases.

• International Journal of Fluid Machinery and Systems
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• v.2 no.3
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• pp.215-222
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• 2009

Jets issuing through small holes in a wall into a freestream has proven effective in the control of flow separation. This technique is known as the vortex generator jet (VGJs) method. If a precursor signal of separation is found, the separation control system using VGJs can be operated just before the onset of separation and the flow field with no separation is always attained. In this study, we measured the flow field and the wall static pressure in a two-dimensional diffuser to find a precursor signal of flow separation. The streamwise velocity measurements were carried out in the separated shear layer and spectral analysis was applied to the velocity fluctuations at some angles with respect to the diffuser. The pattern of peaks in the spectral analysis changes as the divergence angle increases over the angle of which the whole separation occurs. This change in the spectral pattern is related to the enhancement of the growth of shear layer vortices and appears just before the onset of separation. Therefore, the growth of shear layer vortices can be regarded as a precursor signal to flow separation.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.979-986
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• 2018

This paper deals with acoustic echo cancellation using blind signal separation method. This method does not degrade the echo cancellation performance even during double-talk. In the closed echo environment, the mixing model of acoustic signals is multi-channel, so the convolutive blind signal separation method is applied and the mixing coefficients are calculated by using the feedback model without directly calculating the separation coefficients for signal separation. The coefficient update is performed by iterative calculations based on the second-order statistical properties, thus estimates the near-end speech. A number of simulations have been performed to verify the performance of the proposed blind signal separation method. The simulation results show that the acoustic echo canceller using this method operates safely regardless of the presence of double-talk, and the PESQ is improved by 0.6 point compared with the general adaptive FIR filter structure.