• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.629-630
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• 2013

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.04a
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• pp.16-21
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• 1994

For the systems such as ANC(Active Noise Control) systems having auxiliary path after FIR type adaptive filter, Filtered-X LMS algorithm is effective. However behaviors of this algorithm has not been fully understood. The convergence property of this algorithm depends on not only cross correlation matrix between the filtered signals through model and real auxiliary path state solution of weight vector in Filtered-X LMS algorithm is investigated for under-determined case, over-determined case, and nonsingular case. Also, the convergence speed in case of two tone noise is investigated based on the eigenvalue spread of cross correlation matrix.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.172-176
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• 2000

A series of preliminary experiments were carried out to quantify the annoyance are noisiness caused by floor impact noise. From the results of the experiments. the heavy impact source was found to be felt louder and noisier than the light impact source. Measurements of noise were also conducted by a diagnostic system based on the model(the model consists of the autocorrelators and the cross-correlation for signals arriving at two ear entrants) of the human auditory-brain system. Physical factors in the model were calculated by use of the ACF(autocorrelation function) and IACF(interaural cross correlation function) of binaural signals. From the ACF/IACF analysis, it was found that perceived loudness of floor impact noise could be represented by the factors of the ACF/IACF model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.133-140
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• 2004

This study deals with human reaction speed according to human physical conditions (body size) such as head width, thickness, breast width, arm extent, and age. Especially, the results of this study are compared between young and old generation. According to this study, the thickness and extent factor do not have any correlation with human reaction speed, but width factors(head width, breast width, etc) have some correlation with human reaction speed. The result of this study can be used to find fitter person for a special job such as emergency condition job, sports man (because you can find a person having a good talent for it without test). Also, the purpose of this study is to find CNT (Channel Noise Time). The word of CNT is to explain the relation between Channel Noise and working speed. (Channel Noise is a kind of noise happening between the human information transmission channel.)

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.490-496
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• 2020

We present a method to improve the performance of the multi-channel Wiener filter in noisy environment. To build subspace-based multi-channel Wiener filter, in the case of single target source, the target speech component can be effectively estimated in the principal subspace of speech correlation matrix. The speech correlation matrix can be estimated by subtracting noise correlation matrix from signal correlation matrix based on the assumption that the cross-correlation between speech and interfering noise is negligible compared with speech correlation. However, this assumption is not valid in the presence of strong interfering noise and significant error can be induced in the principal subspace accordingly. In this paper, we propose to adjust the principal subspace vector using speech presence probability and the steering vector for the desired speech source. The multi-channel speech presence probability is derived in the principal subspace and applied to adjust the principal subspace vector. Simulation results show that the proposed method improves the performance of multi-channel Wiener filter in noisy environment.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.455-463
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• 2003

Adaptive noise cancellation techniques are ideally suitable for reducing spatially varying noise due to the grain structure of material in ultrasonic nondestructive evaluation. Grain noises have an un-correlation property, while flaw echoes are correlated. Thus, adaptive filtering algorithms use the correlation properties of signals to enhance the signal-to-noise ratio (SNR) of the output signal. In this paper, a multi-stage adaptive noise cancellation (MANC) method using adaptive least mean square error (LMSE) filter for enhancing flaw detection in ultrasonic signals is proposed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.945-953
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• 2005

The purpose of this paper is to develop a linear regression model for the sound quality index of vehicle Interior noise. For this, objective measurement data of the vehicles driving in acceleration was measured. On the basis of analysis, psychoacoustic parameters were extracted and subjective evaluation was performed by noise and vibration expert evaluators. For the subjective evaluation, the paired comparisons and the semantic differential methods were used to evaluate sound quality of vehicle interior noise. By the paired comparison which evaluate two pairs of vehicle interior noise, the preference was estimated. With the semantic differential and the factor analysis, it was evaluated words of two pairs which expressed appropriately the sense of evaluator about noise source. Therefore the characteristics of the sound qualify for the vehicle were differentiated. From the results of both the correlation analysis and the multiple factor regression analysis, the sound quality evaluation model for the sense of human hearing was derived and indexed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.284-292
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• 2008

The active control technique mostly uses the least-mean-square(LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS(FXLMS) algorithm is applied to an active noise control(ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation and experimental results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.169-174
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• 2015

Noise problem that occurs on the road is raising a lot of problems in the economic, social and environmental aspects. The active noise control (ANC) systems based on the filtered-X least mean square(FxLMS) algorithm have a problem with compensating the acoustic feedback of secondary route. However, newly proposed correlation-LMS(CLMS) and expanded CLMS algorithms have slightly much calculation and are minutely behind performance, these have a advantage not in measuring transfer function onerously so that we can easily adapt these in real time. The CLMS and expanded CLMS algorithm was developed to improve the real-time implementation performance under the variable input noise such as road noise environment. In this paper, we compared and analyzed their performance. From the results of the Matlab simulation for an ANC system, it is shown that expanded CLMS algorithms are more convergence speed and keep the desirable performance even in the input of road noise situation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.598-603
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• 2007

The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.