• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.7
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• pp.679-686
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• 2002

Based on the alternating series expansion of error probability function due to phase noise in PSK systems, the performance evaluations for Tikhonov and Gaussian probability density functions were performed in this paper. The range of the signal-to-noise ratio of recovered carrier signal which provides the same dependency between the error performances by Tikhonov function and Gaussian function was analyzed via loss evaluation due to phase noise. The phase noise with 1/f$^2$ characteristic was generated based on the relationship of the phase noise spectral density and the modulation index for frequency modulation signal. Using the generated phase noise as the input signal for digital satellite communication receiver, the performance losses due to the phase noise were measured and evaluated with the analyzed performance characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.280-286
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• 2007

In this paper, the phase noise effects of OFDM transceiver diversity systems were analyzed. Since OFDM communication system is very sensitive to phase noise, the system performance may degrade seriously due to the increase of subcarrier interferences and system noise. Therefore, the phase noise model was suggested and its distribution and power were varied to investigate the effects of phase noise on the system performance. The degree of the system performance degradation depends on the specific diversity structures of transceiver systems. Here, the performances of OFDM systems with two antennas transceiver diversity were analyzed and compared with that of systems with only transmission diversity and without diversity as the phase noise characteristics varied.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.262-269
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• 2023

In this paper, we propose a Linear Prediction (LP) analysis-based feature for detecting Snapping Shrimp (SS) Noise (SSN) in underwater acoustic data. SS is a species that creates high amplitude signals in shallow, warm waters, and its frequent and loud sound is a major source of noise. The proposed feature takes advantage of the characteristic of SSN, which is sudden and rapidly disappearing, by using LP analysis to detect the exact noise interval and reduce the effects of SSN. The error between the predicted and measured value is large and results in effective SSN detection. To further improve performance, a constant false alarm rate detector is incorporated into the proposed feature. Our evaluation shows that the proposed methods outperform the state-of-the-art MultiLayer-Wavelet Packet Decomposition (ML-WPD) in terms of receiver operating characteristic curve and Area Under the Curve (AUC), with the LP analysis-based feature achieving a higher AUC by 0.12 on average and lower computational complexity.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1633-1640
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• 2013

In this paper, noise parameters for high frequency modeling of dual-gate FET are extracted and analyzed. To extract thermal noise parameter of dual gate, noise characteristics are measured by changing input impedance of noise source using Tuner, and the influence of pad parasitic elements are subtracted using open and short dummy structure. Measured results indicated that the dual-gate FET is improved the noise figure by 0.2dB compared with conventional cascode structure FET at 5GHz, and it confirmed that the noise figure has dropped due to reduction of capacitances between the drain and source, gate and drain by simulation and analysis of small-signal parameters.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.809-826
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• 2018

The entropy evaluation method for noise sources is one of the evaluation methods for the random number generator that is the essential element of modern cryptographic systems and cryptographic modules. The primary entropy evaluation methods outside of the country are more suitable to apply to hardware noise sources than software noise sources, and there is a difficulty in quantitative evaluation of entropy by software noise source. In this paper, we propose an entropy evaluation method that is suitable for software noise sources, considering characteristics of software noise sources. We select time-dependent noise sources that are software noise sources of Windows OS, and the heuristic analysis and experimental analysis are performed considering the characteristics of each time-dependent noise source. Based on these analyses, we propose an entropy harvest method from the noise source and the min-entropy estimation method as the entropy evaluation method for time-dependent noise sources. We also show how to use our entropy evaluation method in the Conditioning Component described in SP 800-90B of NIST(USA).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.28-38
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• 2010

In order to remove the noise contained in recorded analog video, it is important to recognize the real characteristics and strength of the noise. This paper presents an efficient training-based noise reduction method for recorded analog video after analyzing the noise characteristics of analog video captured in a real broadcasting system. First we show that there is non-negligible noise correlation in recorded analog video and describe the limitations of the traditional noise estimation and reduction methods based on additive white Gaussian noise (AWGN) model. In addition, we show that auto-regressive (AR) model considering noise correlation can be successfully utilized to estimate and synthesize the noise contained in the recorded analog video, and the estimated AR parameters are utilized in the training-based noise reduction scheme to reduce the video noise. Experiment results show that the proposed method can be efficiently applied for noise reduction of recorded analog video with non-negligible noise correlation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.994-1003
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• 1994

In this paper, a scheme of noise cancellation using spectral subreaction method with single input in an autombile noise environment is proposed. In order to remove the changing automonile noise components form the noisy speech signal, the noise of various states is analyzed and its characteristics are presented. For the decision of speech/nonspeech and the estimation of noise spectrum, a classification function is proposed on the basis of noise analysis. This function presents the precise decision of speech/nonspeech and the optimal estimation of noise spectrum with less computation. As the result of the estimation of noise spectrum by the proposed classification function, the clean speech signal is extracted from the noisy speech signal with high signal-to-ratio.

• Journal of Advanced Navigation Technology
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• v.13 no.3
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• pp.406-411
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• 2009

In this paper, we study the method of noise analysis for analysing TDMA noise in a GSM mobile phone and describe the cause of TDMA noise. And we reduced noise by 9dB, 3.5dB, 6dB, using MIC shielding, equipped bead or capacitance, connected PCB ground based on the difference analysis method, which is one of common noise analysis methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.293-296
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• 2004

본 논문에서는 잡음이 첨가된 선형적으로 혼합된 신호들을 대상으로 뉴우턴법과 할선법의 고정점 알고리즘 각각을 적용할 때 그 분리성능을 비교 검토하였다. 여기서 뉴우턴법은 기울기 변화에 따른 속성을 이용하며, 할선법은 접선의 변화를 이용하는 속성을 가진다. 실험에 이용된 신호는 512$\times$512 픽셀의 2개 2차원 영상이며, 가우스 분포와 라플라시안 분포의 잡음을 이용하였다. 실험 결과, 할선법의 알고리즘이 뉴우턴법보다 잡음에 강인한 특성을 가짐을 알 수 있었다. 한편, 잡음이 첨가되지 않은 경우보다 가우시안 잡음 및 라프라시안 잡음을 첨가한 경우, 절대합 오차값에서 각각 약 23% 및 약 9.7%정도 원영상과의 오차를 보였다.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.658-669
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• 2020

The horizontal-to-vertical spectral ratio (HVSR) analysis is conducted to estimate the site amplification effect and the thickness of the sedimentary layer beneath the measurement site. We investigated the effects of meteorological variations (wind and precipitation rate) and sensor burial depths on HVSR analysis. The HVSR results were unstable when seismographs were exposed on the ground. The HVSR results of ambient noise data measured under strong winds were also unstable. It is recommended to measure the ambient noise at wind speeds of <3 m s-1. Stable HVSR results were obtained when seismographs were buried, regardless of the precipitation rates. The results of this study provide the best observations and optimal weather conditions required to acquire accurate and reliable HVSR results.