• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.41-46
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• 2006

Generation of electricity using wind power has received considerable attention worldwide in recent years. In order to investigate the impacts of the integration of wind farm into utilities' network, various studies have been investigated. One such impact is related to the Critical Clearing Time (CCT) of wind power generation system. This paper reports investigation into the factors that influence the transient behavior of the wind power generation system following network fault conditions. It is shown that CCT can be affected by various factors contributed by the network. Such factors include capacity of wind power, power factor, the length of the interfacing line, etc. This investigation is conducted on a simulated grid-connected wind farm using Digsilent Power Factory.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.105-108
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• 2003

본 논문은 잡음 환경에서의 음성인식을 위하여 음성에 부가된 잡음을 제거하는 방법으로 프레임 단위로 웨이브렛 변환 영역의 표준편차를 활용하여 시간 적응적 임계값을 사용하는 새로운 방법을 제안한다. 웨이브렛 변환영역의 cD1과 cA3의 표준편차 값을 이용하여 임계값을 설정함으로써 음성의 변화에 적응할 수 있도록 하였다. 또한 묵음구간의 잔여 잡음을 제거하기 위한 방법을 제안하였다. 실험을 통하여 제안한 방법이 기존의 웨이브렛 변환과 웨이브렛 패킷 변환을 이용한 잡음제거 방법보다 SNR(Signal to Noise Ratio)과 MSE(Mean Squared Error) 측면에서 향상됨을 확인할 수 있었다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.66-69
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• 2003

웨이블릿 변환이 소개된 후, 웨이블릿 임계치 기법이 신호의 잡음제거에 중요한 효과를 가져왔다. 그러나 웨이블릿 임계치 잡음제거 기법 역시 불연속점 주위에서 의사깁스 현상을 일으키는 단점을 가지고 있다. 본 논문은 웨이블릿 발자국 흔적(Wavelet Footprints) 알고리즘을 소개한다. 웨이블릿의 시간영역에서의 특이점들에 의해 남겨진 흔적이라는 의미를 가지는 발자국 흔적의 새로운 개념을 도입하여 불연속 주위의 의사 깁스 현상을 개선하고자 한다. 제안된 알고리즘은 더 일반적인 신호들로 확장되어지고, 신호의 잡음제거와 같은 문제에 효과적인 해법을 제시 할 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2205-2210
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• 2009

In this paper, the proposed method is a denoising technology by tangent curve interpolation of zero points. The problem of the hard threshold method is improved by the proposed method. The quantity of time fluctuation of the electromagnetic signal as the quantity of electric fluctuation of the natural world or the curve of motion waveform of the fast movement of human extracted using virtual reality is, in fact, complex. Therefore it is important to decide exactly the signal properties as the inflection point for observation signal. In particular, it is necessary to extract the properties after denoising, since the measurement signal of the natural world include some noises. It shows that the noise of the inflection point signal with noise II, noise factor 5, is eliminated by the proposed method, and the result of SNR for the signal is improved 3.4dB than that by the conventional hard threshold.

• The Journal of the Korea institute of electronic communication sciences
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• v.4 no.3
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• pp.190-196
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• 2009

A new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale is proposed. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in level 3 approximation and weighted level 1 detail. Level 3 approximation coefficients represent the voiced sound with low frequency and level 1 detail coefficients represent the unvoiced sound with high frequency. After reducing noise by soft thresholding with the proposed time adapted threshold, there are still residual noises in silent interval. To reduce residual noises in silent interval, a detection algorithm of silent interval is proposed. From simulation results, it can be noticed that SNR and MSE of the proposed algorithm are improved than those of Wavelet transform and than those of Wavelet packet transform.

• Journal of the Korea Computer Industry Society
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• v.6 no.2
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• pp.271-278
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• 2005

This paper proposed a new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in level 3 approximation and weighted level 1 detail. Level 3 approximation coefficients represent the voiced sound with low frequency and level 1 detail coefficients represent the unvoiced sound with high frequency. After reducing noise by soft thresholding with the proposed time adapted threshold, there are still residual noises in silent interval. To reduce residual noises in silent interval, a detection algorithm of silent interval is proposed. From simulation results, it is demonstrated that the proposed algorithm improves SNR and MSE performance more than Wavelet transform and Wavelet packet transform does.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10a
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• pp.694-696
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• 1998

ILP마이크로세서를 위한 스테쥴링 과정에서 메모리 명령어가 프로그램의 임계 경로로에 존재할 경우에 이의 스케쥴링은 성능 향상에 중요한 문제 중에 하나이다. 메모리 명령어의 원활한 코드 이동을 위해서는 장애가 되는 명령어들의 메모리 주소간의 의존성의 분석을 필요로 한다. 본 논문에서는 컴파일 시간에 메모리 주소간의 의존성 분석을 통한 성능 향상도를 VLIW환경 하에서 비교한다. 실험결과. 컴파일 시간에 메모리 주소 모호성 제거기를 사용한 경우 16ALU프로세서에서 정수 벤치마크 프로그램에 대해서 기하 평균으로 약 3.6%의 성능 향상이 가능하다.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.27-35
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• 2003

Because of the lack of translation invariance of wavelet basis, traditional wavelet thresholding denoising leads to pseudo-Gibbs phenomena in the vicinity of discontinuities of signal. In this paper, in order to reduce the pseudo-Gibbs phenomena, wavelet coefficients are thresholded and reconstruction algorithm is implemented through minimizing the total variation of denoising signal using subgradient descent algorithm. Most of experiments were performed under the non-real-time and real-time environments. In the case of non-real-time experiments, the algorithm that this paper proposes was found more effective than that of wavelet hard thresholding denoising by 2.794㏈(SNR) based on the signal to noise ratio. And lots of pseudo-Gibbs phenomena was removed visually in the vicinity of discontinuities. In the case of real-time experiments, the number of iteration was restricted to 60 times considering the performance time. It took 0.49 seconds and most of the pseudo-Gibbs phenomena were also removed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.513-518
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• 2002

This paper presents the new method for removing impulse noise using wavelet. Time and frequency-localization capabilities in denoising can provide excellent specialties comparing with the existing methods, because of including detail information of signal. The method in this paper, using denoising by threshold and slope of signal by wavelet, has superior denoising effect and can recognize edge of original signal. For objective judgement, the test signals are used HeaviSine and DTMF and this paper simulated by test signals which have added to impulse noise of different site individually.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.649-651
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• 2005

본 논문에서는 실제 모바일 환경에서의 멀티미디어 컨텐츠의 요청 패턴을 분석하고 그 결과를 반영한 캐싱 알고리즘을 제안한다. 로그 데이터를 분석한 결과 컨텐츠의 연속적인 요청이 매우 짧은 시간 동안 이루어지는 시간적인 특성을 발견했으며, 컨텐츠의 다른 버전 사이의 요청 시간이 짧음을 통해서 버전별 컨텐츠의 요청이 응집되어 나타남을 확인했다. 제안된 알고리즘에서는 시간적인 특성과 컨텐츠의 인기도 특성을 반영하기 위해 측정 시간 윈도우 내에서 컨텐츠의 요청 횟수를 측정하고, 요청 횟수의 임계값 이상의 컨텐츠에 대해서 유지 시간 단위만큼의 컨텐츠 만료 시간을 정한다. 또한 공간적인 특성을 이용하여 컨텐츠가 캐시에서 제거될 때, 만료시간이 지난 컨텐츠의 다른 버전을 동시에 캐시에서 제거하는 방법을 사용한다 실험 결과 캐시의 크기가 작은 경우 제안된 알고리즘이 기존 알고리즘에 비해 $1-5\%$ 정도 성능향상을 보였다.