• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.1-10
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• 2011

The spectrum sensing is one of the fundamental functions to realize the cognitive radios. One of problems in the spectrum sensing is that the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome the problem, cooperative spectrum sensing method is proposed, which uses a distributed detection model and can increase sensing performance. However, the performance of cooperative spectrum sensing can be still affected by the interference factors such as obstacle and malicious user. Especially, most of cooperative spectrum sensing methods only considered the stationary primary user. In the ubiquitous environment, however the mobile primary users should be considered. In order to overcome the aforementioned problem, in this paper we propose a robust spectrum detection method based on localization where we estimate the location of the mobile primary user, and then based on the location and transmission range of primary user we detect interference users if there are, and then the local sensing reporting from detected interference users are excluded in the decision fusion process. Through simulation, it is shown that the sensing performance of the proposed scheme is more accurate than that of conventional other schemes

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.391-394
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• 1998

본 논문에서는 극심한 가산 잡음에 의해 손상된 음성 신호를 스펙트럼 차감법으로 개선할 때, 잡음 스펙트럼 추정을 위한 무음 구간 추정 방법을 제안한다. 스펙트럼 차감법은 잡음을 효과적으로 제거한다고 알려져 있으나, SNR 0 dB 이하의 잡음 환경에서는 무음 구간의 검출이 힘들어 잡음 스펙트럼 추정치의 정확도가 저하된다. 일반화 스펙트럼 차감법의 과차감(oversubtraction)과 잡음 스펙트럼 추정을 반복하여 얻은 무음 구간은 SNR -10 dB~ 0 dB의 낮은 SNR에서도 비교적 정확하며, 프레임 에너지를 이용한 무음 검출 방법에 비해 향상된 성능을 보였다.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.46-55
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• 2001

In this paper, a new voice activity detection method estimating SNR of enhanced speech with extended spectral subtraction (ESS) is proposed. Voice activity detection is performed by putting an second Wiener filter behind an Wiener filter used in the ESS to estimate speech and noise power of output signal of first Wiener filter. The proposed voice activity detection method does not require many computational loads and performs well under severe input SNR. Boll's spectral substraction algorithm with proposed voice activity detection was compared to ESS under several noise environment having different time-frequency distributions. During speech and non-speech activity, performance of Boll's spectral substraction algorithm with proposed voice activity detection is superior to that of ESS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.47-54
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• 2019

An improved method of spectrum detection algorithm for mass spectrum analysis system is proposed. In the conventional spectrum detection algorithm that utilizes the results of the linear approximation and quadratic curve fitting on the ion signal block of each mass index, it is possible to reduce the detection error in the mass spectrum detection by further improving the condition of eliminating the invalid ion signals. Also, the proposed method can reduce the estimation error of the peak value of the mass spectrum by using the result of quadratic curve fitting for the effective ion signal block in which the peak position error is corrected. To evaluate the effectiveness of the proposed method, computer simulations were carried out step by step using the measured ion signal. Also, by comparing the rate of false detection for several inputs, the proposed method showed better detection performance than the conventional method.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.29-32
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• 2000

본 논문에서는 미지의 반송파주파수를 가진 협대역 신호의 존재를 광대역에서 검출하는 문제를 고려하였다. DFT 전력 스펙트럼을 평균화하여 주파수 영역에서 Neyman-Pearson criterion을 사용하여 신호를 검출하는 방법을 사용하였다. 평균화된 DFT 스펙트럼의 통계적 특성과 검출 threshold 및 검출 확률을 분석하여 보았다.

• Journal of Radiation Protection and Research
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• v.32 no.1
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• pp.9-13
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• 2007

From HPGe calibration spectrum of liquid mixed source in cylindrical vial, we developed simulated spectrum for spectrum analysis education. It is the spectrum that combine peaks separated from measured spectrum. After that, spectrum removed statistical variation of channel counts. Statistical fluctuation of the spectrum is made by Box-Muller function. The spectrum contains 18 peaks. The peak's centroid and area were defined exactly. Developed spectra are calibration spectrum, sample spectrum, background spectrum and spectra for efficiency correction for geometry and cascade coincidence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.666-674
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• 2019

In the mass spectrum of the mass spectrometer, the spectrum of the low peak adjacent to the spectrum having the high peak value is connected to each other and thus the separation is difficult. This inter-spectral overlap causes degradation of the mass spectral detection performance and resolution. In this paper, we propose a method to improve the mass spectrum detection performance and peak accuracy of residual gas analyzer. The type discrimination according to the characteristics of the ion signal block and the pre-correction for the peak position error can separate and detect the spectrum of the low peak connected to the adjacent spectra. To verify the performance of the proposed method, we compared the proposed method with the conventional method in simulations using actual ion signals obtained from the mass spectrometer under development.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.85-94
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• 2011

Spectrum sensing is one of the most important technologies in cognitive radio. Although many studies have considered energy detection technique as the spectrum sensing technique, noise variance in practical systems is difficult to estimate accurately. Thus, in the real system, the probability of false alarm will not be maintained constant. In this paper, with considering that the cognitive radio does not know the primary user's signal, we propose a new spectrum sensing scheme which can operate without the information of noise variance. Through simulations, we show that the proposed scheme can detect spectrum with the condition of unknown noise information and have robustness for the change of noise variance.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.60-67
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• 2007

The spectrum sensing is important for decision of using frequency band. It checks the frequency band for cognitive radio system. In this paper, we apply autocorrelation function to the energy detection method. We use the autocorrelation function to improve the performance of spectrum sensing method based on the energy detection method. This method is different from cyclostationary process method where parameters such as the mean or the autocorrelation function are time-varying periodically. And we propose improved method that is robust in poor radio environment. If the proposed method applies for sensing in the cognitive radio system, it will have the structural simplicity and the fast computation of spectrum sensing.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.86-91
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• 1999

본 논문에서는 유성/무성/묵음 분류기와 주파수 스펙트럼 비교를 통하여 음소 경계 검출기를 구현하였다. 음소경계 검출은 음성 인식, 합성 및 분석 둥의 분야에서 매우 중요하다 유성/무성/묵음 분류기를 이용하여 유성음으로 판별되는 구간은 스펙트럼 비교를 통하여 음소 단위로 세분하였고 무성음으로 판별되는 구간은 한국어의 음성 특성을 고려하여 하나의 음소 단위로 간주하였다. 유성음 구간에 대한 스펙트럼 비교는 수정된 Itakura-Saito distance measure 와 Euclidean MFCC(Mel Frequency Cepstrum Coeffcients) distance measure를 사용하였고 비교 프레임은한 프레임을 건너 윈 경우가 가장 결과가 좋았다. 최종적으로 평균 음소 길이 정보를 이용하여 음소의 경계로 검출된 구간을 더 세분하거나 통합하였다. 유성/무성/묵음 분류기의 경우는 사무실에서 녹음한 고립단어에 대하여 $94.247\%$의 정확도를 보였고 음소 경계 검출의 경우는 $72.8\%$의 정확도를 보였다.