• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.581-587
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• 2004

Conventional power spectrum methods based on FFT, AR method are not appropriate for analyzing biomedical signals whose spectral characteristics change rapidly. On the other hand, time-frequency analysis has more desirable characteristics of a time-varying spectrum. In this study, we investigated the spectral components of heart rate variability(HRV) in time-frequency domain using time frequency analysis methods. In the various time-frequency kernels functions, we studied the suitable kernels for the analysis of HRV using synthetic HRV signals. First, we evaluated the time/frequency resolution and cross term reduction of various kernel functions. Then, from the instantaneous frequency, obtained from time-frequency distribution, the method extracting frequency components of HRV was proposed. Subjects were 17 healthy young men. A coin-stacking task was used to induce mental stress. For each subjects, the experiment time was 3 minutes. Electrocardiogram, measured during the experiment, was analyzed after converted to HRV signal. In the results, emotional stress of subjects produced an increase in sympathetic activity. Sympathetic activation was responsible for the significant increase in the LF/HF ratio. Subjects were divided into two groups with task ability. Subjects who have higher mental stress have lack of task ability.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.87-96
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• 2014

In this paper, we propose a directionally adaptive aliasing and noise removal using dictionary learning based on space-frequency analysis. The proposed aliasing and noise removal algorithm consists of two modules; i) aliasing and noise detection using dictionary learning and analysis of frequency characteristics from the combined wavelet-Fourier transform and ii) aliasing removal with suppressing noise based on the directional shrinkage in the detected regions. The proposed method can preserve the high-frequency details because aliasing and noise region is detected. Experimental results show that the proposed algorithm can efficiently reduce aliasing and noise while minimizing losses of high-frequency details and generation of artifacts comparing with the conventional methods. The proposed algorithm is suitable for various applications such as image resampling, super-resolution image, and robot vision.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2146-2147
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• 2011

전기화재의 원인인 아크 신호는 전류 돌입형, 비선형 및 전류 단속형 부하들의 정상상태와 유사한 전류파형을 갖는다. 이러한 부하들에서 아크를 정확하게 검출하기 위해서는 아크 유무를 정확히 판단 할 수 있는 시스템이 필요하며 이러한 시스템에서 아크검출을 정확히 하는 필터가 중요하다. 본 논문에서는 UL1699의 직렬 아크 발생장치로 아크를 발생시키고 시간 및 주파수 영역에서 아크 전류파형을 분석하였다. 분석결과 아크전류파형은 시간영역에서는 영점전류의 처짐 현상(shoulder)이 발생하고 주파수영역에서는 60Hz의 고조파 성분을 제외한 전대역의 주파수에 걸쳐서 스펙트럼이 증가하였다. 본 논문에서 제시된 아크 검출용 필터는 이러한 특징들 중 주파수 영역의 특징을 검출한다.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.245-247
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• 2020

본 논문에서는 DUT(Device Under Test) 및 PHIL(Power Hardware-in-the-Loop) 시뮬레이터의 스위칭 주파수 비 및 PWM 위상차에 의하여 발생할 수 있는 문제를 분석하였다. 또한, DUT 인버터의 PWM 특성을 고려한 디지털 필터를 적용하여 PHIL 시뮬레이터의 운전 영역을 확대하였다. 디지털 필터는 DUT 스위칭 주파수의 고조파 성분만을 선택적으로 제거하여 PHIL 스위칭 주파수에 무관하게 일정한 시뮬레이션 결과를 생성할 수 있다. 분석한 내용과 디지털 필터의 변경으로 인한 PHIL 시뮬레이터의 특성은 다양한 조건에서 시행된 실험을 통하여 검증하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.949-954
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• 2013

We measured and analyzed the brain waves to observe the characteristics of human drowsiness. The basic method is to analyze the EEG(Electroencephalography) signals from subjects according to the frequency bands. It has been reported that alpha waves are related to a wakefulness state, an eye closure state and a state that begins to sleep. In this study, therefore, we restricted the frequency band for analyzing to between 8 and 13Hz called brain's alpha waves. We observed which components had a stronger influence on human drowsiness among the restricted frequency band and represented the experimental results to analyze using the power spectrum method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2170-2178
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• 2014

In this paper, electroencephalographic (EEG) signal of one among subjects measured biosignal with visual evoked stimuli inducing the concentration was analyzed to detect the changes in the attention status during attention task fulfillment from January to February, 2011. The independent component analysis (ICA) was applied to EEG signals to isolate the attention related innate source signal within the brain and Electroculogram (EOG) artifact from measured EEG signals at the scalp. The consecutive accumulation of short time Fourier transformed (STFT) attention source signal with excluded EOG artifact can enhance the regular depiction of EPOCH graph and spectral color map representing time-varying pattern. The extracted attention indices associated with somatosensory rhythm (SMR: 12-15 Hz), and theta wave (4-7 Hz) increase marginally over time. Throughout experimental observation, the ICA with STFT can be used for the assessment of participants' status of attention.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.112-122
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• 2009

In this paper, we present a novel space-frequency adaptive image restoration approach using vaguelette-wavelet decomposition (VWD). The proposed algorithm classifies a degraded image into flat and edge regions by using spatial information of the wavelet coefficient. For reducing the noise we perform an adaptive wavelet shrinkage process. At edge region candidates, we adopt entropy approach for estimating the noise and remove it by using relative between sub-bands. After shrinking wavelet coefficients process, we restore the degraded image using the VWD. The proposed algorithm can reduce the noise without affecting the sharpness details. Based on the experimental results, the proposed algorithm efficiently proved to be able to restore the degraded image while preserving details.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.37-45
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• 1998

In this paper, the different frequency component and time informations from an EMI signal are extracted simultaneously using a wavelet transform and the results of transform in the time and frequency domain are analyzed. Frequencies are extracted from the EMI signal by performing the multiresolution analysis using the Daubechies-4 filter coefficients and the time information through the results of wavelet transform. We have tried the correlation analysis to evaluate the results of wavelet transform. We have chosen the optimal wavelet function for an object signal by comparing the transformed results of various wavelet functions and verified the simulation examples of waveform and harmonic analysis using a wavelet transform. We have proved the denoising effect to the EMI signal using the soft thresholding technique.

• Aerospace Engineering and Technology
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• v.3 no.2
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• pp.25-33
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• 2004

In this paper, we briefly introduce the micro-vibration test bench of KARI and the test and analysis method of RWA(Reaction Wheel Assembly) micro-vibration. The micro-vibration of RWA is measured on a KISTLER dynamic plate which can measure the time signal of 6 DOF simultaneously up to 400Hz. Measured data are extensively evaluated with respect to the wheel spin rate to identify the complicate wheel dynamic characteristics, and the static/dynamic unbalances are estimated from the extracted first harmonic component as a part of evaluation process. The estimated static and dynamic unbalances. 0.79gcm and 17.4gcm² respectively. The structural resonance mode and two rocking modes observed as a results of its frequency analysis. Several higher order harmonic components observed, which come from its rotor shape as well as the wheel bearing characteristics.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.85-86
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• 2016

본 논문은 스위칭 주파수 스펙트럼 분석에 기반한 모듈형 병렬 양방향 DC-DC 컨버터의 전류분배 제어방법을 제안한다. 병렬 DC-DC 컨버터 각 모듈의 전류분배 균일도 향상은 동작안정성 확보, 효율 및 신뢰성 향상을 위해 매우 중요한 요소이다. 드룹 제어의 적용을 통해 별도의 통신연결 없이 각 병렬모듈간 전류 분배량 제어가 가능하지만, 선로 저항의 차이나 측정 소자의 편차가 발생할 경우 각 모듈간 균일한 전류분배가 어려운 문제가 존재한다. 각 모듈간 전류분배를 위해 각 개별모듈의 입력 전류에 존재하는 스위칭 주파수 성분만을 분석하여 병렬 모듈 사이의 전류분배 차이를 검출하고, 그 차이를 최소화 하도록 드룹 이득을 단계적으로 조절하는 제어 알고리즘을 제안한다. 제안된 제어 알고리즘은 에너지 저장장치와 연계된 380V급 DC 배전 시스템 모델을 대상으로 검증하였다.