• Progress in Medical Physics
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• v.11 no.2
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• pp.141-146
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• 2000

Power spectrum analysis is a powerful noninvasive tool for quantifying autonomic nervous system activity. In this paper, We developed a measuring system for Autonomic Nervous Activity by using power spectrum analysis method to obtain the activities of autonomic nervous system. This system adopt a isolated power for patient's safety. In this system, Two output signal is obtained - R-R interval time variability and Respiration time variability. Time variability is use to find out some disease related to Autonomic Nervous System. Experimental tested range is 30 ～ 240 BPM for ECG and 15～80 BPM for Respiration.

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.97-103
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• 2014

In spectrum sensing, there is a tradeoff between the probability of missed detection and the probability of a false alarm according to the value of the sensing threshold. Therefore, it is important to determine the sensing threshold suitable to the environment of cognitive radio networks. In this study, we consider a cognitive radio-based ad hoc network where secondary users directly communicate by using the same frequency band as the primary system and control their transmit power on the basis of the distance between them. First, we investigate a condition in which the primary and the secondary users can share the same frequency band without harmful interference from each other, and then, propose an algorithm that controls the sensing threshold dynamically on the basis of the transmit power of the secondary user. The analysis and simulation results show that the proposed sensing threshold control algorithm has low probabilities of both missed detection and a false alarm and thus, enables optimized spectrum sharing between the primary and the secondary systems.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.151-156
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• 1989

Lung sound analyer which can provide an objective diagnosis of patients with pulmonary and bronchial disorders is designed. For the purpose of power spectrum analysis, adaptive digital filtering technique and TM - S320C25 DSP chip is used. As a results, adaptive lattice Wiener filter could eliminate heart sounds with a few of 10th order and on the distribution of power spectrum each patterns has shown in normal vescicular breathy from 100 Hz to 200 Hz, in crackle sound from 100 Hz to 400 Hz, in wheeze sound from 150 Hz to 600 Hz.

• Biomolecules & Therapeutics
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• v.8 no.1
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• pp.63-72
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• 2000

We intended to show some basic requirements for spectrum analysis of electroencephalogram (EEG) by visualizing the differences of the results according to different values of some parameters for analysis. Spectrum analysis is the most popular technique applied for the quantitative analysis of the electroen- cephalographic signals. Each step from signal acquisition through spectrum analysis to presentation of parameters was examined with providing some different values of parameters. The steps are:(1) signal acquisition; (2) spectrum analysis; (3) parameter extractions; and (4) presentation of results. In the step of signal acquisition, filtering and amplification of signal should be considered and sampling rate for analog-to-digital conversion is two-time faster than highest frequency component of signal. For the spectrum analysis, the length of signal or epoch size transformed to a function on frequency domain by courier transform is important. Win dowing method applied for the pre-processing before the analysis should be considered for reducing leakage problem. In the step of parameter extraction, data reduction has to be considered so that statistical comparison can be used in appropriate number of parameters. Generally, the log of power of all bands is derived from the spectrum. For good visualization and quantitative evaluation of time course of the parameters are presented in chronospectrogram.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.3
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• pp.123-128
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• 2020

Analysis of the 2016 Gyeongju earthquake and the 2017 Pohang earthquake showed the characteristics of a typical high-frequency earthquake with many high-frequency components, short time strong motion duration, and large peak ground acceleration relative to the magnitude of the earthquake. Domestic nuclear power plants were designed and evaluated based on NRC's Regulatory Guide 1.60 design response spectrum, which had a great deal of energy in the low-frequency range. Therefore, nuclear power plants should carry out seismic verification and seismic performance evaluation of systems, structures, and components by reflecting the domestic characteristics of earthquakes. In this study, high-frequency amplification factors that can be used for seismic verification and seismic performance evaluation of nuclear power plant systems, structures, and equipment were analyzed. In order to analyze the high-frequency amplification factor, five sets of seismic time history were generated, which were matched with the uniform hazard response spectrum to reflect the characteristics of domestic earthquake motion. The nuclear power plant was subjected to seismic analysis for the construction of the Korean standard nuclear power plant, OPR1000, which is a reactor building, an auxiliary building assembly, a component cooling water heat exchanger building, and an essential service water building. Based on the results of the seismic analysis, a high-frequency amplification factor was derived upon the calculation of the floor response spectrum of the important locations of nuclear power plants. The high-frequency amplification factor can be effectively used for the seismic verification and seismic performance evaluation of electric equipment which are sensitive to high-frequency earthquakes.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.178-184
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• 2007

The EEG signal in general can be categorized as the Alpha wave, the Beta wave, the Theta wave, and the Delta wave. The alpha wave, showed in stable state, is the dominant wave for a human EEG and the beta wave displays the excited state. The subject of this paper was to recognize the stable state of EEG quantitatively using wavelet transform and power spectrum analysis. We decomposed EEG signal into the alpha wave and the beta wave in the process of wavelet transform, and calculated each power spectrum of EEG signal, using Fast Fourier Transform. And then we calculated the stable state quantitatively by stable state ratio, defined as the power spectrum of the alpha wave over that of the beta wave. The study showed that it took more than 10 minutes to reach the stable state from the normal activity in 69 % of the subjects, 5 -10 minutes in 9%, and less than 5 minutes in 16 %.

• Journal of Korea Water Resources Association
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• v.38 no.6 s.155
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• pp.439-448
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• 2005

This paper introduces the wavelet transform that was improved by the fourier transform to assess periodicities and trends, we assessed propriety with examples of two monthly precipitation data, annual precipitation, SOI index and SST index. The wavelet transform can effectively assess the power spectrum corresponding to frequency as maintaining chronological characteristics. The results of the analysis using the wavelet transform showed that the monthly precipitation have the strongest power spectrum near that of 1 year, and the annual precipitation represent the dominated spectrum in the band of 2-8 years. Also, the SOI index and SST index indicate the strongest power spectrum in the band of 2-8 years.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.137-145
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• 2011

In this paper, we modeled digital M/W transmission channel by frequency non-selective fading channel and analyzed the power spectrum magnitude of digital M/W transmission systems adopting OFDM modulation scheme through simulation. From the simulation results, it was found that deep does not appear in the specified fixed bandwidth under the AWGN environment. Also, lower power spectrum magnitude was shown in frequency non-selective fading channel than that in AWGN channel. Futhermore, the power spectrum magnitude value became more lowered when carrier frequency and vehicle speed became higher.

• ETRI Journal
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• v.33 no.2
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• pp.279-282
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• 2011

Coexistence analysis is extremely important in examining the possibility for spectrum sharing between orthogonal frequency-division multiplexing (OFDM)-based international mobile telecommunications (IMT)-Advanced and other wireless services. In this letter, a new closed form method is derived based on power spectral density analysis in order to analyze the coexistence of OFDM-based IMT-Advanced systems and broadcasting frequency modulation (FM) systems. The proposed method evaluates more exact interference power of IMT-Advanced systems in FM broadcasting systems than the advanced minimum coupling loss (A-MCL) method. Numerical results show that the interference power is 1.3 dB and 3 dB less than that obtained using the A-MCL method at cochannel and adjacent channel, respectively. This reduces the minimum separation distance between the two systems, which eventually saves spectrum resources.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.767-774
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• 2022

In this paper raw spectrum data were analyzed to suggest the moving forward of performance evaluation and quality control of wind profilers of four manufacturers operating in South Korea. For the analysis, the profile of the spectrum averaged by season and the profile of four statistical values (minimum, average, median, and maximum) calculated by Power Spectrum Density (PSD) were used. The quality of spectrum data was the best for LAP-3000, followed by YKJ3, PCL-1300, and CLC-11-H. In Cheorwon and Chupungnyeong, where PCL-1300 was installed, the variability of the spectrum due to ground clutter and non-meteorological signals was large, so ground clutter removal and signal processing such as moving average and multi-peak were required. In Gunsan and Paju, where CLC-11-H was installed, DC (Direct Current) bias and propagation folding were found, so it is necessary to remove the DC bias and limit the effective altitude for observation.