• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.110-114
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• 2012

We studied on the nondestructive evaluation of the elastic wave signal of SiC ceramics and SiC/SiC composite ceramics under monotonic tensile loading. The elastic wave signal of cross and unidirectional SiC/SiC composite ceramics were obtained by pencil lead method and bending test. It was applied for the time-frequency method which used by the discrete wavelet analysis algorithm. The time-frequency analysis provides time variation of each frequency component involved in a waveform, which makes it possible to evaluate the contribution of SiC fiber frequency. The results were compared with the characteristic of frequency group from SiC slurry and fiber. Based on the results, if it is possible to shift up and design as a higher frequency group, we will can make the superior material better than those of exiting SiC/SiC composites.

• 전자공학회논문지C
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• 제34C권1호
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• pp.51-58
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• 1997

In passive sonar, the frequency spectrum of a sound radiated by underwater moving targets is composed of a broadband nonuniform background noise and narrowband discrete tonals. To detect the tonals, the background noise is estimated and removed. Using the existing algorithms that estimate the background noise, a week tonals are not detected. Because a freuqency line that is formed by tonals which are being extracted continuously is a feture of the target, we are nessesory to efficiently detect the tonals that compose the frequncy line. In this paper, we propose an efficient neural network that can remove automatically the background and detect the even errl tonals, and we extract the frequency line feature on the spectrogram by the proposed algorithm. The experimental results for a ship's radiated sound show a better performance in comparison with the existing TPM algorithm.

• 디지털융복합연구
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• 제12권11호
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• pp.309-316
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• 2014

본 논문에서는 초점/비초점 영상에서 깊이 지도를 효율적으로 추출하기 위하여 그래프 컷(Graph Cut)과 이산 웨이블릿 변환(Discrete Wavelet Transform)을 이용한 깊이 지도 생성 기법을 제안한다. 제안하는 방법은 우선 해당 영상을 영역 별로 처리하기 위해 그래프 컷 방법으로 각 픽셀 간의 유사도를 이용하여 분할한다. 그 다음 분할 영역을 레이블링 하여 원 영상의 분할 영역 정보를 생성한다. 그리고 이산 웨이블릿 변환을 이용하여 원 영상 내의 주파수 정보를 나타내는 LL, LH, HH, HL 부대역(Subband)을 생성한다. 마지막으로 4개의 부대역 중 영상의 초점/비초점 영역을 분석할 단서가 되는 HH, HL 대역을 이용하여 주파수 지도를 생성한 뒤 분할 영역에 따라 깊이 정보를 계산함으로써 깊이 지도를 추출한다. 제안하는 방법은 초점 정보인 블러(Blur)의 양에 따라 동적인 깊이의 할당이 가능하여 효율적인 깊이 지도의 생성이 가능하였다. 실험으로 PSNR(Peak Signal to Noise Ratio) 방법을 통해 제안하는 방법의 성능을 평가하였다.

• 한국전자통신학회논문지
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• 제18권6호
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• pp.1103-1108
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• 2023

본 논문에서는 음향신호의 배경잡음을 감쇠하기 위한 새로운 알고리즘을 제안한다. 이 알고리즘은 이산 웨이블릿 변환(DWT: Discrete Wavelet Transform) 후 기존의 적응필터를 대신 FNN(: Full-connected Neural Network) 심층학습 알고리즘을 이용하여 잡음감쇠 성능을 개선하였다. 입력신호를 단시간 구간별로 웨이블릿 변환한 다음 1024-1024-512-neuron FNN 딥러닝 모델을 이용하여 잡음이 포함된 단일입력 음성신호로부터 잡음을 제거한다. 이는 시간영역 음성신호를 잡음특성이 잘 표현되도록 시간-주파수영역으로 변환하고 변환 파라미터에 대해 순수 음성신호의 변환 파라미터를 이용한 지도학습을 통하여 잡음환경에서 효과적으로 음성을 예측한다. 본 연구에서 제안한 잡음감쇠시스템의 성능을 검증하기 위하여 Tensorflow와 Keras 라이브러리를 사용한 시뮬레이션 프로그램을 작성하고 모의실험을 수행하였다. 실험 결과, 제안한 심층학습 알고리즘을 사용하면 기존의 적응필터를 사용하는 경우보다 30%, STFT(: Short-Time Fourier Transform) 변환을 사용하는 경우보다는 20%의 평균자승오차(MSE: Mean Square Error) 개선효과를 얻을 수 있었다.

• 한국소음진동공학회논문집
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• 제22권3호
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• pp.291-297
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• 2012

Conventional Fourier analysis can give only limited information about the dynamic characteristics of nonstationary signals. Instead, time-frequency analysis is widely used to investigate the nonstationary signal in detail. Several time-frequency analysis methods are compared for a typical acoustic emission burst generated during the impact between a ferrite ceramic and aluminum plate. This AE burst is inherently nonstationary and random containing many frequency contents, which leads to severe interference between cross terms in bilinear convolution type distributions. The smoothing and reassignment processes can improve the readability and resolution of the results. Spectrogram and scalogram of the AE burst are obtained and compared to get the characteristics information. Renyi entropies are computed for various bilinear time-frequency transforms to evaluate the randomness. These bilinear transforms are reassigned by using the improved algorithm in discrete computation.

• 전기전자학회논문지
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• 제19권4호
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• pp.465-471
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• 2015

An LC-tuned sinusoidal voltage-controlled oscillator (VCO) using temperature-stable linear operational transconductance amplifiers (OTAs) is presented. Its architecture is based on Hartley oscillator configuration, where the inductor is active one realized with two OTAs and a grounded capacitor. Two diode limiters are used for limiting amplitude. A prototype oscillator built with discrete components exhibits less than 3.1% nonlinearity in its current-to-frequency transfer characteristic from 1.99 MHz to 39.14 MHz and $220ppm/^{\circ}C$ frequency stability to the temperature drift over 0 to $75^{\circ}C$. The total harmonic distortion (THD) is as low as 4.4 % for a specified frequency-tuning range. The simulated phase noise of the VCO is about -108.9 dBc/Hz at 1 MHz offset frequency in frequency range of 0.4 - 46.97 MHz and property of phase noise of VCO is better than colpitts-VCO.

• 한국전자파학회논문지
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• 제20권1호
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• pp.21-28
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• 2009

DFT(Discrete Fourier Transform) 확산 방식의 OFDM(Orthogonal Frequency Division Multiplexing) 통신 시스템은 PAPR(Peak-to-Average Power Ratio) 저감에 매우 효과적인 시스템이며, 3GPP LTE($3^{rd}$ Generation Partnership Project Long Term Evolution)의 상향 링크에 SC-FDMA(Single Carrier-Frequency Division Multiple Access)에 사용된다. SC-FDMA는 일반적으로 OFDM 시스템보다 위상잡음과 직교 불균형으로 인한 ICI(Inter-Carrier Interference)에서 더 성능 열화가 발생하며, 등화기에 심각한 영향을 미친다. 그러므로 본 논문에서는 상향 링크에서 신호 전송 시 발생하는 위상잡음과 직교 불균형(IQ Imbalance: In-phase/Quadrature Imbalance), 그리고 전력 증폭기(HPA: High Power Amplifier)의 백-오프 특성에 따른 영향을 분석하고, ICI 성분을 제거할 수 있는 효과적인 등화 알고리듬을 제시한다. 제안된 등화기는 FDE(Frequency Domain Equalizer) 방식을 기반으로 설계하였으며, 기존의 PNS(Phase Noise Suppression) 알고리듬을 FDE에 사용될 수 있도록 수정하고 개선하여 위상 잡음과 직교 불균형으로 인한 ICI를 보상한다. 시뮬레이션 결과를 통하여 back-off 5.5 dB 상태에서 위상 잡음 $0.06\;rad^2$, 위상 에러 5도, 진폭 에러 0.005인 경우, 위상 잡음과 직교 불균형을 보상하여 SNR=14 dB 정도에서 $BER=10^{-4}$의 성능을 만족할 수 있다.

• ETRI Journal
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• 제32권3호
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• pp.390-394
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• 2010

In this paper, we propose a new super-resolution technique based on interpolation of the high-frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The proposed technique uses DWT to decompose an image into different subband images. Then the high-frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new super-resolved image by using inverse DWT. The proposed technique has been tested on Lena, Elaine, Pepper, and Baboon. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. For Lena's image, the PSNR is 7.93 dB higher than the bicubic interpolation.

• 한국소음진동공학회논문집
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• 제18권9호
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• pp.952-960
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• 2008

Fan noise prediction method is presented for air conditioning, automobile and electronic cooling system applications where fan acts as an internal equipment having very complicated flow interaction with other various system components. The internal flow paths and distribution in the fan-applied systems such as computer or air conditioner are analyzed by using the FNM(flow network modeling). Fan noise prediction method comprises two models for the discrete frequency noise due to rotating steady aerodynamic lift and blade interaction and for the broadband noise due to turbulent boundary layer and wake vortex shedding. Based on the fan operation point predicted from the FNM analysis results and fan design parameters, the present far noise model predicts overall sound pressure level and spectrum. The predictions for the flow distribution, the fan operation and the noise level in air cooling system by the present method are well agreed with 3-D CFD and actual noise test results.

• IEIE Transactions on Smart Processing and Computing
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• 제3권2호
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• pp.41-51
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• 2014

This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.