• 제목/요약/키워드: spectral ratio method

검색결과 302건 처리시간 0.027초

Application of advanced spectral-ratio radon background correction in the UAV-borne gamma-ray spectrometry

  • Jigen Xia;Baolin Song;Yi Gu;Zhiqiang Li;Jie Xu;Liangquan Ge;Qingxian Zhang;Guoqiang Zeng;Qiushi Liu;Xiaofeng Yang
    • Nuclear Engineering and Technology
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    • 제55권8호
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    • pp.2927-2934
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    • 2023
  • The influence of the atmospheric radon background on the airborne gamma spectrum can seriously affect researchers' judgement of ground radiation information. However, due to load and endurance, unmanned aerial vehicle (UAV)-borne gamma-ray spectrometry is difficulty installing upward-looking detectors to monitor atmospheric radon background. In this paper, an advanced spectral-ratio method was used to correct the atmospheric radon background for a UAV-borne gamma-ray spectrometry in Inner Mongolia, China. By correcting atmospheric radon background, the ratio of the average count rate of U window in the anomalous radon zone (S5) to that in other survey zone decreased from 1.91 to 1.03, and the average uranium content in S5 decreased from 4.65 mg/kg to 3.37 mg/kg. The results show that the advanced spectral-ratio method efficiently eliminated the influence of the atmospheric radon background on the UAV-borne gamma-ray spectrometry to accurately obtain ground radiation information in uranium exploration. It can also be used for uranium tailings monitoring, and environmental radiation background surveys.

주파수 영역에서의 인공지진과 자연지진의 식별 (Discrimination of Natural Earthquakes and Explosions in Spectral Domain)

  • 김성균;김명수
    • 자원환경지질
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    • 제36권3호
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    • pp.201-212
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    • 2003
  • 한반도 남동부의 경상분지에 한국지질자원연구원의 지진관측망을 비롯한 관측소들이 급격히 증가함에 따라, 지진관측의 능력이 최근에 들어 크게 향상되었다. 그러나, 빈번한 중소규모의 화약발파에 의한 진동이 다수 관측되고 있다. 따라서, 이 지역에서 자연지진과 발파에 의한 인공지진의 식별이 중요한 문제로 부상하였다. 이 지역에서의 인공지진과 자연지진의 적절한 식별법을 확립하기 위하여 소규모의 지역지진 43개와 이에 대응되는 인공지진 43개를 선정하였다. 이 연구에서는 주파수 영역에서 Pg파, Sg파 및 Lg파의 스펙트럼 진폭비를 이용하는 기법들이 폭 넓게 검토되었다. 그들 중 Pg/Lg 스펙트럼 진폭비를 이용하는 방법이 가장 좋은 식별법으로 나타났다. 또한, 식별능력을 향상시키기 위하여 Pg/Lg 스펙트럼비에 다변량 판별분석법을 적용하였다. 거리보정이 안된 수직성분에 비하여 거리에 대한 감쇠효과를 보정한 3성분의 Pg/Lg비에 판별분석법을 적용했을 때의 판별능력은 뚜렷한 증가를 보인다. 주파수 대역 4-l4Hz의 범위에서, 거리 보정한 3성분의 Pg/Lg비에 대한 판별분석의 결과 총 분류비율은 0.89%에 불과한 것으로 나타난다.

서브밴드 백색화 필터를 이용한 부공간 잡음 제거 (Subspace Speech Enhancement Using Subband Whitening Filter)

  • 김종욱;유창동
    • 한국음향학회지
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    • 제22권3호
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    • pp.169-174
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    • 2003
  • 본 논문에서는 서브밴드 백색화 필터를 이용한 새로운 부공간 잡음제거 방법을 제안하였다. 기존의 부공간 접근방법에서는 백색 잡음을 가정하거나, 유색 잡음에 대한 전처리로서 백색화 필터를 사용하였다. 백색화 필터를 서브밴드로 나누어 처리함으로써, 제안된 방법은 잔여잡음을 줄이면서 신호 왜곡의 상한값을 최소화하도록 설계하였다. 또한 서브밴드 백색화 필터를 도입함으로써 부공간 잡음제거 방법에서 약점으로 지적되는 것 중의 하나인 Karhunen-Loeve(KL) 영역에서의 주파수 해상도를 높일 수 있었다. 실험결과에 의하면 제안된 방법은 Ephraim에 의해 제안된 방법 부공간 잡음 제거 방법이나, Boll에 의해 제안된 주파수 차감법에 비해 구분 신호대 잡음 비 (SNRseg: segmental signal-to-noise ratio), 음성의 인지적 성능 평가 (PESQ: perceptual evaluation of speech quality)를 고려하였을 때 향상된 성능을 보였다.

LANSAT TM자료에 의한 광화대조사 응용기법개발 (Remote Sensing Application for the Mineralized Zone Using Landsat TM Data)

  • 姜必鍾;智光薰;曺民肇;崔映燮;Choi, Young Sup
    • 대한원격탐사학회지
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    • 제2권2호
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    • pp.79-94
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    • 1986
  • TM data, which have better resolution in spatial and spectral than MSS data, were used for this study, and several Image Processing Techniques (IPT) were examined for finding the best IPT to fit to lineament extraction and mineralized zone mapping. The Ryeongnam area was selected as test area, because the area is one of major mineralized zones in Korea and its hydrothermal alteration zone is wider and deeper than other areas. The spatial filtering method is most optimum one for limeament extraction: that is, the directional spatial filtering is most efficient to detect N-S, E-W direction lineaments on the image, and the high boost filtering can be applied for mapping all direction lineaments. The ratio method was selected for detecting altered zone. It is possible to make several tens combinations in ratio with 7 bands of TM data, but considering spectral characteristics of each band of TM to the geological meterials and vegetation, the band 4/band 3(A), band 5/band 7(B), and B/A ratio methods were chosen among them. The 5/7 ratio image did not show clearly the altered area due to noise from vegetation cover, so the 4/3 ratio imae was used for trying to decrease the effect of vegetation. As a result the B/A ratio image showed quite nicely the altered zone of the test area. In conclusion, the spatial filtering is the best image processing techniques for lineament mapping, and the B/A ratio image in TM data is useful for the mineralized zone mapping.

Robust Voice Activity Detection Using the Spectral Peaks of Vowel Sounds

  • Yoo, In-Chul;Yook, Dong-Suk
    • ETRI Journal
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    • 제31권4호
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    • pp.451-453
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    • 2009
  • This letter proposes the use of vowel sound detection for voice activity detection. Vowels have distinctive spectral peaks. These are likely to remain higher than their surroundings even after severe corruption. Therefore, by developing a method of detecting the spectral peaks of vowel sounds in corrupted signals, voice activity can be detected as well even in low signal-to-noise ratio (SNR) conditions. Experimental results indicate that the proposed algorithm performs reliably under various noise and low SNR conditions. This method is suitable for mobile environments where the characteristics of noise may not be known in advance.

음성 및 잡음 인식 알고리즘을 이용한 환경 배경잡음의 제거 (Reduction of Environmental Background Noise using Speech and Noise Recognition)

  • 최재승
    • 한국정보통신학회논문지
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    • 제15권4호
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    • pp.817-822
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    • 2011
  • 본 논문에서는 먼저 신경회로망의 학습에 오차역전파 학습 알고리즘을 사용하여 각 프레임에서의 음성 및 잡음 구간의 검출에 의한 음성인식 알고리즘을 제안한다. 그리고 신경회로망에 의하여 음성 및 잡음 구간의 검출에 따라서 각 프레임에서 잡음을 제거하는 스펙트럼 차감법을 제안한다. 본 실험에서는 제안한 음성인식알고리즘의 성능을 원음성에 백색잡음 및 자동차 잡음을 부가하여 인식율을 평가한다. 또한 인식시스템에 의하여 검출된 음성 및 잡음 구간을 이용하여 각 프레임에서의 스펙트럼 차감법에 의한 잡음제거의 실험결과를 나타낸다. 잡음에 의하여 오염된 음성에 대하여 신호대잡음비를 사용하여 본 알고리즘이 유효하다는 것을 확인한다.

Investigation on site conditions for seismic stations in Romania using H/V spectral ratio

  • Pavel, Florin;Vacareanu, Radu
    • Earthquakes and Structures
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    • 제9권5호
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    • pp.983-997
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    • 2015
  • This research evaluates the soil conditions for seismic stations situated in Romania using the horizontal-to-vertical spectral ratio (HVSR). The strong ground motion database assembled for this study consists of 179 analogue and digital strong ground motion recordings from four intermediate-depth Vrancea seismic events with $M_w{\geq}6.0$. In the first step of the analysis, the influence of the earthquake magnitude and source-to-site distance on the H/V curves is evaluated. Significant influences from both the earthquake magnitude and hypocentral distance are found especially for soil class A sites. Next, a site classification method proposed in the literature is applied for each seismic station and the soil classes are compared with those obtained from borehole data and from the topographic slope method. In addition, the success and error rates of this method are computed and compared with other studies from the literature. A more in-depth analysis of the H/V results is performed using data from seismic stations in Bucharest and a comparison of the free-field and borehole H/V curves is done for three seismic stations. The results show large differences between the free-field and the borehole curves. As a conclusion, the results from this study represent an intermediary step in the evaluation of the soil conditions for seismic stations in Romania and the need to perform more detailed soil classification analysis is highly emphasized.

주파수 차지확률을 이용한 음성검출기 제안 (Speech detection using the probability of spectral occupancy)

  • Hong, Seong-Bong;Ki, Tae-Young;Kim, Nam-Soo;Kim, Taejeong
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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    • pp.171-174
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    • 2000
  • In this paper, we improve statistical-model-based speech detector using the probability that a speech occupies a frequency bin. While the previous method assumes speech energy occupies all the frequency components and use them with equal weights in the likelihood ratio test for speech detection, the proposed method assumes speech energy occupies just some frequency componets and use them with different weights in accordance with the probabilities of spectral occupancy in the test. The probability is iteratively up-dated for speech frames to contribute to the likelihood ratio test. The proposed method well reflects the characteristic distribution of speech spectrum, and yields better detection performance.

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광대역 정규 프로세스에 대한 주파수 영역 기반 피로해석법의 적용성에 관한 연구 I : 레일리 PDF (Study on Applicability of Frequency Domain-Based Fatigue Analysis for Wide Band Gaussian Process I : Rayleigh PDF)

  • 정준모;김경수;남지명;구정본;김민수;심용래;엄항섭
    • 대한조선학회논문집
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    • 제49권4호
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    • pp.350-358
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    • 2012
  • This paper deals with accuracy of accumulated fatigue damage estimation using stochastic fatigue analysis method based on Rayleigh PDF. From full scale measurement data on an 8100TEU container vessel, zero-order spectral moments for wave- and vibration-induced energy spectral densities are determined on the probability level of 99%. 80 simulation cases in total are prepared according to the variation of ratio of zero-order spectral moments and center frequency of vibration ESD. By using inverse Fourier transformation and rainflow cycle counting for the combined ESD of wave and vibration, exact fatigue damages are derived. Fatigue damages in frequency domain based on Rayleigh PDF show large conservativeness compared to exact fatigue damages in times domain. The main cause of the excessive conservativeness is analyzed by two aspects: ratio of zero crossing and peak frequencies and ratio of initial zero order spectral moments and zero order spectral moments from rainflow stress range distributions. Finally, a guideline of applicability of Rayleigh PDF is proposed for wide band processes.

Speech Processing System Using a Noise Reduction Neural Network Based on FFT Spectrums

  • Choi, Jae-Seung
    • Journal of information and communication convergence engineering
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    • 제10권2호
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    • pp.162-167
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    • 2012
  • This paper proposes a speech processing system based on a model of the human auditory system and a noise reduction neural network with fast Fourier transform (FFT) amplitude and phase spectrums for noise reduction under background noise environments. The proposed system reduces noise signals by using the proposed neural network based on FFT amplitude spectrums and phase spectrums, then implements auditory processing frame by frame after detecting voiced and transitional sections for each frame. The results of the proposed system are compared with the results of a conventional spectral subtraction method and minimum mean-square error log-spectral amplitude estimator at different noise levels. The effectiveness of the proposed system is experimentally confirmed based on measuring the signal-to-noise ratio (SNR). In this experiment, the maximal improvement in the output SNR values with the proposed method is approximately 11.5 dB better for car noise, and 11.0 dB better for street noise, when compared with a conventional spectral subtraction method.