• The Journal of the Acoustical Society of Korea
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• v.33 no.1
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• pp.54-59
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• 2014

Identification of RTF (Relative Transfer Function) between sensors is essential to multichannel speech enhancement system. In this paper, we present an approach for estimating the relative transfer function of speech signal. This method adapts a CASA (Computational Auditory Scene Analysis) technique to the conventional OM-LSA (Optimally-Modified Log-Spectral Amplitude) based approach. Evaluation of the proposed approach is performed under simulated stationary and nonstationary WGN (White Gaussian Noise). Experimental results confirm advantages of the proposed approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.9 no.2
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• pp.62-69
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• 1984

The performance of direct-sequence spread spectrum(DS-SS) receiver may be enhanced by using the digital whitening filter. In this paper, the hard limited feedback whitening filter that whiten the interference and noise alone is proposed to obtain the additional resistance to narrowband interference. The recursive solution for the calculation of tap weights is presented and the expression for SNR and BER is derived and compared with the conventional digital whitening filter. As the result of computer simulation it is proved that the error performance is improved considerably.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1
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• pp.9-16
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• 1998

본 논문에서는 낮은 비트율 CELP 음성 부호화기의 장구간 예측기의 성능 향상 방 법을 제안한다. 비트율을 낮추기 위해서는 분석 구간의 길이가 길어져야하며 이에 따라 장 구간 예측기의 성능이 저하되어 장구간 예측 후에도 준 주기성 성분이 상당량 존재하므로 백색 잡음으로 구성된 통계 코드북만으로는 이를 모델링하기 어려워진다. 제안 방법에서는 다중 대역 필터와 다중 펄스열을 이용하여 한 번 더 필터링(이차 장구간 예측)함으로써 장 구간 예측 후의 신호가 통계 코드북에 적합한 백색 잡음 형태로 되도록 모델링한다. 제안된 방법의 성능을 평가하기 위해 4.8kbps 비트율로 양자화한 후, 기존에 제안된 같은 전송률의 MBCELP와 DoD-CELP와 비교하였다. 실험 결과 제안된 방법이 기존 부호화기들에 비해 주/객관적인 음질에서 우수한 성능을 보여준다.

• Journal of Fisheries and Marine Sciences Education
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• v.12 no.2
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• pp.191-198
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• 2000

An experiment was carried out to obtain the fundamental data on the auditory thresholds of fishes for catching method using audible frequency sound, the auditory thresholds of dusky spinefoot Siganus fuscescens(Houttuyn) were measured in the presence of masking noise in the spectrum level range of 74 - 83dB re $1{\mu}Pa/{\sqrt{Hz}}$ by heartbeat conditioning technique using pure tones coupled with a delayed electric shock. The auditory critical ratios were about 23 - 34dB at measurement frequency range. The ratio increased almost linearly with increasing frequency from 200 to 500Hz. The noise spectrum level at the start of masking was about 61 - 73dB within the measurement frequency range. This suggests that hearing of dusky spinefoot is masked in the natural environment with the noise spectrum level above 70dB. The sound pressure level of which the signal sound of 100Hz is recognized by dusky spinefoot under the white noise of 70dB is above 98dB and the critical ratio of them is above 23dB.

• The Journal of the Acoustical Society of Korea
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• v.12 no.1E
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• pp.5-11
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• 1993

본 논문에서는 페이딩 채널에서 백색 가우시안 잡음과 임펄스성 잡음이 부가된 디지털 신호를 복원하기 위하여 적응 LMS알고리즘과 RLS 알고리즘을 사용하여 TDL 등화기, 결정 궤환 등화기, 그리고 격자 등화기의 성능을 평가하고 비교하였다. 오차 성능 분석 결과, 페이딩이 존재하고 임펄스성과 가우스성 잡음이 존재하는 채널에서 10-3BER을 얻기 위해서, 격자 등화기는 LMS이 등화기보다 3.0dB, RLS TDL 등화기보다 3.9dB의 신호대 잡음비(SNR)여유를, 그리고 LMS DFE 등화기보다 0.5dB, RLS DFE등화기보다 -0.5dB의 SNR 여유를 갖음을 확인하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.739-741
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• 2004

영상에서 Edge는 영역의 경계를 표현하며. 특징으로는 픽셀 밝기의 불연속점을 나타낸다. 이러한 Edge를 찾아내는 Edge detection은 설러 가지 영상 처리 기법에서 유용하게 사용되고 있다. 현재까지 많은 알고리즘들이 제안되었으며. 이 논문에서는 이러한 알고리즘들에 대한 장단점을 파악하고, 미분 연산자를 이용한 Sobel, Prewitt. Roberts. Laplacian, 그리고 Canny 마스크를 이용한 윤곽선 검출방법과 Discrete Sing에ar Convolution (DSC) 알고리즘을 이용한 윤곽선 검출방법을 백색 가우시안 잡음 환경과 비 잡음 환경에서 비교해 보았다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.181-187
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• 2013

When there are background noises or some people speaking at the same time, a human's auditory sense has the ability to listen the target speech signal with a specific purpose through Auditory Scene Analysis. The CASA system with human's auditory faculty system is able to segregate the speech. However, the performance of CASA system is reduced when the CASA system fails to determine the correct position of the speech. In order to correct the error in locating the speech on the CASA system, voice activity detection algorithm is proposed in this paper, which is a combined auditory scene analysis with PAR(Periodic to Aperiodic component Ratio). The experiments have been conducted to evaluate the performance of voice activity detection in environments of white noise and car noise with the change of SNR 15~0dB. In this paper, by comparing the existing algorithms (Pitch and Guoning Hu) with the proposed algorithm, the accuracy of the voice activity detection performance has been improved as the following: improvement of maximum 4% at SNR 15dB and maximum 34% at SNR 0dB for white noise and car noise, respectively.

• Korean Chemical Engineering Research
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• v.62 no.1
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• pp.118-124
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• 2024

A neural network is utilized for preprocessing of de-noizing in electrocardiogram signals, retinal images, seismic waves, etc. However, the de-noizing process could provoke increase of computational time and distortion of the original signals. In this study, we investigated a neural network architecture to analyze measurement data without additional de-noizing process. From the dynamical behaviors of DNA in aqueous solution, our neural network model aimed to predict the mole fraction of each DNA in the solution. By adding white noise to the dynamics data of DNA artificially, we investigated the effect of the noise to neural network's predictions. As a result, our model was able to predict the DNA mole fraction with an error of O(0.01) when signal-to-noise ratio was O(1). This work can be applied as a efficient artificial intelligence methodology for analyzing DNA related to genetic disease or cancer cells which would be sensitive to background measuring noise.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.34-36
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• 2001

본 논문에서는 모델 기반의 잡음 보상 방법인 PMC (parallel model combination)를 온라인상에서 적용하는 방법에 관해 논한다. PMC는 파라미터 보상시 미리 계산된 잡음 모델을 필요로 하며 파라미터 보상에 많은 연산을 요구하므로 온라인으로 모델 파라미터를 보상하기가 어렵다. 본 논문에서는 이러한 문제를 해결하기 위해 기존에 제안된 온라인 모델 보상 방법을 살펴보고, 기존 방법에서 보상 시간 문제로 제외한 PMC의 공분산 보상을 비교적 적은 연산량으로 수행하여 인식성능을 더욱 향상시켰다. 고립 숫자음 인식시스템에 백색 잡음을 SNR 0, 5, 10 dB로 가산한 평가 자료로 실험한 결과, 제안한 방식은 PMC를 적용한 경우에 비해 모델 적응 시간은 적게 걸리면서도 기존의 온라인 모델 보상 방법에 비해 평균 10%의 인식률 향상을 보였다.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.48-55
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• 2001

A novel method to reduce additive non-stationary noise is proposed. The method requires neither the information about noise nor the estimate of the noise statistics from any pause regions. The enhancement is performed on a band-by-band basis for each time frame. Based on both the decision on whether a particular band in a frame is speech or noise dominant and the masking property of the human auditory system, an appropriate amount of noise is reduced using spectral subtraction. The proposed method was tested on various noisy conditions (car noise, Fl6 noise, white Gaussian noise, pink noise, tank noise and babble noise) and on the basis of comparing segmental SNR with spectral subtraction method and visually inspecting the enhanced spectrograms and listening to the enhanced speech, the method was able to effectively reduce various noise while minimizing distortion to speech.