• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.855-859
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• 2012

This study derives a generalized PSD formula in the LTV phase noise theory for noisy oscillators. The derived formula analytically proves that the LTV phase noise theory can predict the conservation of the power in the noisy oscillation signals. Additionally, the derived formula allows the theory to account for the behavior of the power spectrum over the entire frequency range including the regions around higher harmonics as well as fundamental frequency.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.11
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• pp.22-27
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• 2011

In spectrum sensing, an energy detector compares the energy of a received signal with a predetermined detection threshold and decides whether a primary user is active or not in a licensed frequency band. Here the detection threshold is related to the noise power level in the band. Most previous works on energy detection have assumed that the noise power is exactly known a priori. However, this assumption does not hold in practice since there may be some uncertainty about the noise power. So it is necessary to investigate its effects on the performance of energy detection for spectrum sensing. In this paper, we analyze the effects using the residue theorem for contour integral and present the associated numerical results.

• Journal of radiological science and technology
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• v.39 no.1
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• pp.99-105
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• 2016

The noise power spectrum (NPS) is one of the most general methods for measuring the noise amplitude and the quality of an image acquired from a uniform radiation field. The purpose of this study was to compare different NPS methodologies by using megavoltage X-ray energies. The NPS evaluation methods in diagnostic radiation were applied to therapy using the International Electro-technical Commission standard (IEC 62220-1). Various radiation therapy (RT) devices such as TrueBeam$^{TM}$(Varian), BEAMVIEW$^{PLUS}$(Siemens), iViewGT(Elekta) and Clinac$^R$ iX (Varian) were used. In order to measure the region of interest (ROI) of the NPS, we used the following four factors: the overlapping impact, the non-overlapping impact, the flatness and penumbra. As for NPS results, iViewGT(Elekta) had the higher amplitude of noise, compared to BEAMVIEW$^{PLUS}$ (Siemens), TrueBeam$^{TM}$(Varian) flattening filter, Clinac$^{R}$iXaS1000(Varian) and TrueBeam$^{TM}$(Varian) flattening filter free. The present study revealed that various factors could be employed to produce megavoltage imaging (MVI) of the NPS and as a baseline standard for NPS methodologies control in MVI.

• Journal of IKEEE
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• v.17 no.4
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• pp.559-563
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• 2013

This paper analytically proves the equivalence between two main oscillator phase noise theories, which are based on the ISF, and Floquet vector, respectively. For this purpose, this study obtains the power spectral density matrix from the ISF-based phase noise theory. As a result, one can prove that the power spectral density matrix obtained from the ISF-based phase noise theory is essentially equivalent to the power spectral density matrix presented by the Floquet vector-based phase noise theory, which manifests the equivalence of the two main theories. This study is intended to provide deeper insight into the relations between the two main theories.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.222-228
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• 2010

In this paper, we propose a new approach to noise estimation incorporating spectral deviation with soft decision scheme to enhance the intelligibility of the degraded speech signal in non-stationary noisy environments. Since the conventional noise estimation technique based on soft decision scheme estimates and updates the noise power spectrum using a fixed smoothing parameter which was assumed in stationary noisy environments, it is difficult to obtain the robust estimates of noise power spectrum in non-stationary noisy environments that spectral characteristics of noise signal such as restaurant constantly change. In this paper, once we first classify the stationary noise and non-stationary noise environments based on the analysis of spectral deviation of noise signal, we adaptively estimate and update the noise power spectrum according to the classified noise types. The performances of the proposed algorithm are evaluated by ITU-T P. 862 perceptual evaluation of speech quality (PESQ) under various ambient noise environments and show better performances compared with the conventional method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.124-127
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• 2003

본 논문에서는 초광대역 무선 통신에 안티포달 펄스 신호를 이용하고, 기존의 초광대역 시간도약 모노펄스 통신에서 규칙적인 펄스를 전송할 때 발생하는 전력 스펙트럼에서의 에너지 스파크 현상을 완화시키기 위하여 의사잡음 부호와 왈쉬 부호를 사용하였을 때의 전력 스펙트럼 특성을 비교, 분석하였다. 그 결과, 초광대역 안티포달 임펄스 통신에서의 두 가지 부호 방식의 이용으로 에너지 스파크 현상이 완화되고 고속의 시간도약 부호를 이용하지 않더라도 완만한 전력스펙트럼 특성을 얻을 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.89-97
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• 2012

In this paper, we propose a novel approach to noise power estimation for speech enhancement in noisy environments. The method based on IMCRA (improved minima controlled recursive averaging) which is widely used in speech enhancement utilizes a rough VAD (voice activity detection) algorithm which excludes speech components during speech periods in order to improves the performance of the noise power estimation by reducing the speech distortion caused by the conventional algorithm based on the minimum power spectrum derived from the noisy speech. However, since the VAD algorithm is not sufficient to distinguish speech from noise at non-stationary noise and low SNRs (signal-to-noise ratios), the speech distortion resulted from the minimum tracking during speech periods still remained. In the proposed method, minimum power estimate obtained by IMCRA is modified by SMT (spectral minima tracking) to reduce the speech distortion derived from the bias of the estimated minimum power. In addition, in order to effectively estimate minimum power by considering the distribution characteristic of the speech and noise spectrum, the presented method combines the minimum estimates provided by IMCRA and SMT depending on the weighting factor based on the subband. Performance of the proposed algorithm is evaluated by subjective and objective quality tests under various environments and better results compared with the conventional method are obtained.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.199-206
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• 2017

Environmental noise can degrade the performance of speech recognition system. This paper presents a procedure for performing cepstrum based feature compensation to make recognition system robust to noise. The approach is based on direct compensation of spectral tilt to remove effects of additive noise. The noise compensation scheme operates in the cepstral domain by means of calculating spectral tilt of the log power spectrum. Spectral compensation is applied in combination with SNR-dependent cepstral mean compensation. Experimental results, in the presence of white Gaussian noise, subway noise and car noise, show that the proposed compensation method achieves substantial improvements in recognition accuracy at various SNR's.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.3
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• pp.116-123
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• 1999

SMPS는 수위칭 소자를 이용하여 효과적으로 전력을 변환시킨다. 여기에서 가장 중요한 파라미터가 스위칭 주파수이다. 스위칭 주파수를 증가시킴에 따라 전원장치의 소형경량화가 가능하다. 그러나 기존 PWM 컨버터에서는 치명적인 단점으로 스위칭 주파수를 증가시킴에 따라 스위칭 손실 및 EMI 문제를 야기한다. 특히 SMPS의 동작은 상당히 큰 di/dt와 dv/dt에 기인한 EMI 전도성 잡음을 발생시킨다. EMI를 감소시키는 방법들로는 고전적이고 고가인 입력필터 혹은 주 전력단에 능동필터를 첨가하는 방법 등이 있어 왔다. 본 논문에서는 DC/DC 포워드 컨버터에 대해 EMI 잡음 발생원 및 잡음 경로를 분석하였다. SMPS에서 방출되는 전도성 잡음은 스위칭 주파수와 그 고주파 주파수에 집중되어 있다. 따라서 본 연구에서는 일정 출력전압에는 큰 영향 없이 스위칭 주파수를 약간씩 변조하게 되는 RPWM 제어를 통하여 전도성 잡음의 주파수 대역을 측면대역으로 분사시키어 전체 첨두치를 저감시키고, 고조파 스펙트럼을 개선할 수 있다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.555-560
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• 2013

This paper first proposes a classification algorithm which detects a voiced, unvoiced, and silence signal using distance measure, logarithm power and root mean square methods at each frame, then a spectrum subtraction algorithm based on a subband filter. The proposed algorithm subtracts spectrums of white noise and street noise from noisy signal based on the subband filter at each frame. In this experiment, experimental results of the proposed spectrum subtraction algorithm demonstrate using the speech and noise data of Aurora-2 database. Based on measuring the speech-to-noise ratio (SNR), experiments confirm that the proposed algorithm is effective for the speech by contaminated the noise. From the experiments, the improvement in the output SNR values was approximately 2.1 dB and 1.91 dB better for white noise and street noise, respectively.