• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.38-44
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• 1999

In this paper, a new spectral subtraction technique with two microphone inputs is proposed. In conventional spectral subtraction using a single microphone, the averaged noise spectrum is subtracted from the observed short-time input spectrum. This results in reduction of mean value of noise spectrum only, the component varying around the mean value remaining intact. In the method proposed in this paper, the short-time noise spectrum excluding the speech component is estimated by introducing the blocking matrix used in Griffiths-Jim-type adaptive beamformer with two microphone inputs, combined with the spectral compensation technique. A simulation was conducted to verify the effectiveness of the method.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.227-233
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• 2015

In this paper, we propose music and voice separation using kernel sptectrogram models backfitting based on log-spectral amplitude estimator. The existing method separates sources based on the estimate of a desired objects by training MSE (Mean Square Error) designed Winer filter. We introduce rather clear music and voice signals with application of log-spectral amplitude estimator, instead of adaptation of MSE which has been treated as an existing method. Experimental results reveal that the proposed method shows higher performance than the existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.597-599
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• 2012

음성인식 및 음성신호처리 분야에서 신경회로망은 음성인식의 카테고리 분류에 주로 이용되고 있다는 점에 착안하여, 본 논문에서는 신경회로망의 입력신호로 음성의 진폭 스펙트럼 및 위상 스펙트럼을 사용한 잡음억제를 위한 신경회로망을 제안한다. 본 논문에서 제안한 알고리즘은 고속 푸리에 변환(Fast Fourier Transform, FFT)에 의한 진폭 스펙트럼 및 위상 스펙트럼을 사용한 잡음억제 신경회로망을 이용하여 각 프레임에서 FFT 스펙트럼을 추정한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1867-1872
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• 2016

In the area of digital signal processing, it is necessary to improve the quality of the speech signal after removing the background noise which exists in a various real environments. The important thing to consider when removing the background noise acoustically is that to solve the problem, depending on the information of the human auditory mechanism is mainly the amplitude spectrum of the speech signal. This paper introduces the characteristics of a frequency-weighted spectrum shaping filter for the extraction of the amplitude spectrum of the speech signal with the primary purpose. Therefore, this paper proposes an algorithm using the methods of a Wiener filter and the frequency-weighted spectrum shaping filter according to the acoustic model, after extracted the amplitude spectral information in the noisy speech signal. The spectral distortion (SD) output of the proposed algorithm is experimentally improved more than 5.28 dB compared to a conventional method.

• Journal of the Korean Geophysical Society
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• v.6 no.1
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• pp.25-29
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• 2003

We suggest a method that vectorially composes 3-component earthquake records in the frequency domain, to reduce the uncertainties in the analysis of the Fourier amplitude spectrum. The use of the Fourier amplitude spectrum composed from 3 components has two advantages. First, it provides a more accurate estimate of seismic moment by eliminating the vector-partition term that appears in individual component. Second, it provides more accurate estimates of seismic moment, corner frequency, high-frequency decay constant($χ$) .etc., by enhancing the shape of the Fourier amplitude spectrum. The latter is especially useful in the analysis of small earthquakes with low signal-to-noise ratios.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.512-514
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• 2011

본 논문에서는 스펙트럼 회복의 수단으로써 신경회로망을 사용하여 푸리에변환(FFT) 진폭성분 및 위상성분을 복원하는 알고리즘을 제안한다. 본 논문에서는 먼저 각 프레임의 FFT 진폭성분들을 유성음 구간과 무성음 구간으로 검출한 후, 유성음 및 무성음 구간에 대해서 각 프레임의 FFT 진폭성분들을 저역, 중역 및 고역으로 각각 분리한 후에 각 대역의 FFT 진폭성분들을 저역용 신경회로망(NN), 중역용 NN, 그리고 고역용 NN의 입력으로 하여 각 NN에 학습시킴으로써 최종 FFT 진폭성분들을 구한다. 본 실험에서는 Aurora2 데이터베이스를 사용하여 FFT의 진폭성분을 복원하는 잡음제거의 알고리즘을 사용하여 여러 잡음에 대해서 본 알고리즘의 유효성을 실험적으로 확인한다.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.967-970
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• 2014

An efficient peak detection algorithm in magnitude spectrum is proposed to distinguish the M-frequency shift keying(FSK) signals from other digitally modulated signal. In addition, recognition of the modulation order estimation of FSK signals is also studied based on the fact that the magnitude spectrum of FSK signals reveals the number of peaks equal to the modulation order. When no a priori information about the signals, we utilize the histogram of the magnitude spectrum to determine the threshold which is important factor in peak detection algorithm. The simulation results show high probability of classification under 500 symbols and signal-to-noise ratio(SNR) higher than 4dB.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.4
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• pp.112-118
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• 2013

The selection of appropriate ground motions and reasonable modification are becoming increasingly critical in reliable prediction on seismic performance of structures. A widely used amplitude scaling approach is not sufficient for robust structural evaluation considering a site specific seismic hazard because only one spectral value is matched to the design spectrum typically at the structural fundamental period. Hence alternative approaches for ground motion selection and modifications have been suggested. However, there is no means to evaluate such methodologies yet. In this study, it is focused to describe the main questions resided in the amplitude scaling approach and to propose a regression model for structural damage as point of comparison. Spectrum compatible approach whose resulting spectrum matches the design spectrum at the entire range of the structural period is considered as alternative to be compared to the amplitude scaling approach. The design spectrum is generated according to ASCE7-05.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.2
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• pp.88-98
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• 1998

A waveform for shock response spectrum test on a shaker is synthesized using wavelets such that a specified shock response spectrum of a test profile is achieved. The parameters of a wavelet are center frequency, amplitude, number of half cycles, delay and polarity. The amplitude of each wavelet component is iteratively adjusted so a specified shock response spectrum is matched. The waveform so synthesized is regarded as a reference acceleration waveform for a shaker shock response spectrum test. The author proposes the use of a long duration and low peak waveform. The usefulness of this approach is illustrated with some examples.

• Geophysics and Geophysical Exploration
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• v.17 no.3
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• pp.137-146
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• 2014

This study presents a procedure for discrimination of artificial events from earthquakes occurred in and around the Korean Peninsula using data set in the Wonju KSRS seismograph network, Korea. Two training sets representing natural and artificial earthquakes were constructed with 150 and 56 events, respectively, with high signal to noise ratio. A frequency band, Pg(4-6 Hz)/Lg(5-7 Hz), which is optimal for the discrimination of seismic sources was derived from the two-dimensional grid of Pg/Lg spectral amplitude ratio. The corrections for the effects of earthquake magnitude and hypocentral distance were carried out for improvement of discrimination capability. For correcting the effect of magnitude dependence due to the inverse proportionality of corner frequency to seismic moment, the Brune's source spectrum was subtracted from the observation spectrum. The spectrum was corrected using the optimal damping coefficient to remove damping effect with the hypocentral distance. The effect of locally varying spectrum ratio was cancelled correcting variation of wave propagation along the ray path. The performance in discrimination between training sets of natural and artificial events was compared using the Mahalanobis distance in each step of correction. The procedure of magnitude, distance, and path corrections show clear improvements of the discrimination results with increasing Mahalanobis distance, from 1.98 to 3.01, between two training sets.