• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 추계학술대회
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• pp.109-112
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• 1995

This paper is a study on the detection of the significant point in ECG signal. ECG signal consists of two components; one is high frequency component to be detected and the other is low frequency component to be removed. AR model is appropriate for modelling and removing the low frequency component. AR model coefficients are updated by artificial neural network algorithm. We can remove the background noise(low frequency) by passing through the AR filter. The remaining signals which include high frequency noise are sent to the matched filter to pass only the signal which we want to extract. The template used in matched filter is updated adaptively.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2002년도 춘계학술대회논문집
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• pp.213-217
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• 2002

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2218-2230
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• 2012

In this paper, we propose an efficient channel delay estimation method for orthogonal frequency-division multiplexing (OFDM) systems, especially over doubly-selective fading channels which are selective in both the symbol time domain and subcarrier frequency domain. For the doubly-selective fading channels in single frequency network (SFN), long and strong echoes exist and thus the conventional discrete Fourier Transform (DFT) based channel delay estimation system often fails to produce the exact channel delay profile. Based on the analysis of the discrete-time frequency response of the channel impulse response (CIR) coefficients in the DFT-based channel delay estimation system, we develop a method to effectively extract the true CIR from the aliased signals by employing a simple narrow-band low-pass filter (NB-LPF). The performance of the proposed system is verified using the COST207 TU6 SFN channel model.

• 대한전기학회논문지:전력기술부문A
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• 제54권4호
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• pp.165-171
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• 2005

Electromagnetic transient simulation can be used to model complex non-linearities that very difficult to represent adequately in the frequency domain. This problem is greatly reduced with the use of frequency dependent network equivalents for the linear part of the system. S-domain rational function fitting techniques for representing frequency dependent equivalents have been developed using Least Squares Fitting(LSF). However it does not suffer the implementation error that exited in this work as it ignored the instantaneous term. This paper presents the formulation for developing 2 port Frequency Dependent AC System Equivalent(FDACSE) with the instantaneous term in S-domain and illustrates its use. This 2 port FDNE have been applied to the New Zealand AC system. The electromagnetic transient package PSCAD/EMTDC is used to assess the transient response of the 2 port (FDACSE) developed with Norton Equivalent network. The study results have indicated the robustness and accuracy of 2 port FDACSE for electromagnetic transient studies.

• Journal of Communications and Networks
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• 제13권6호
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• pp.664-677
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• 2011

In order to control interference and improve spectrum efficiency in the femtocell and macrocell overlaid system (FMOS), we propose a joint frequency bandwidth dynamic division, clustering and power control algorithm (JFCPA) for orthogonal-frequency-division-multiple access-based downlink FMOS. The overall system bandwidth is divided into three bands, and the macro-cellular coverage is divided into two areas according to the intensity of the interference from the macro base station to the femtocells, which are dynamically determined by using the JFCPA. A cluster is taken as the unit for frequency reuse among femtocells. We map the problem of clustering to the MAX k-CUT problem with the aim of eliminating the inter-femtocell collision interference, which is solved by a graph-based heuristic algorithm. Frequency bandwidth sharing or splitting between the femtocell tier and the macrocell tier is determined by a step-migration-algorithm-based power control. Simulations conducted to demonstrate the effectiveness of our proposed algorithm showed the frequency-reuse probability of the FMOS reuse band above 97.6% and at least 70% of the frequency bandwidth available for the macrocell tier, which means that the co-tier and the cross-tier interference were effectively controlled. Thus, high spectrum efficiency was achieved. The simulation results also clarified that the planning of frequency resource allocation in FMOS should take into account both the spatial density of femtocells and the interference suffered by them. Statistical results from our simulations also provide guidelines for actual FMOS planning.

• 한국수산과학회지
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• 제49권2호
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• pp.214-223
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• 2016

Joint time-frequency images of the broadband acoustic echoes of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution (SPWVD). The acoustic features were extracted by changing the sliced window widths and dividing the time window by a 0.02-ms interval and the frequency window by a 20-kHz bandwidth. The 22 spectrum amplitudes obtained in the time and frequency domains of the SPWVD images were fed as input parameters into an artificial neural network (ANN) to verify the effectiveness for species-dependent features related to fish species identification. The results showed that the time-frequency approach improves the extraction of species-specific features for species identification from broadband echoes, compare with time-only or frequency-only features. The ANN classifier based on these acoustic feature components was correct in approximately 74.5% of the test cases. In the future, the identification rate will be improved using time-frequency images with reduced dimensions of the broadband acoustic echoes as input for the ANN classifier.

• 전기학회논문지
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• 제57권4호
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• pp.729-734
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• 2008

Vibroarthrographic(VAG) signals, emitted by human knee joints, are non-stationary and multi-component in nature and time-frequency distributions(TFD) provide powerful means to analyze such signals. The objective of this paper is to classify VAG signals, generated during joint movement, into two groups(normal and patient group) using the characteristic parameters extracted by time-frequency transform, and to evaluate the classification accuracy. Noise within TFD was reduced by singular value decomposition and back-propagation neural network(BPNN) was used for classifying VAG signals. The characteristic parameters consist of the energy parameter, energy spread parameter, frequency parameter, frequency spread parameter by Wigner-Ville distribution and the amplitude of frequency distribution, the mean and the median frequency by fast Fourier transform. Totally 1408 segments(normal 1031, patient 377) were used for training and evaluating BPNN. As a result, the average value of the classification accuracy was 92.3(standard deviation ${\pm}0.9$)%. The proposed method was independent of clinical information, and showed good potential for non-invasive diagnosis and monitoring of joint disorders such as osteoarthritis and chondromalacia patella.

• 한국통신학회논문지
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• 제28권12C호
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• pp.1250-1257
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• 2003

영상은 일반적으로 에지 영역과 평탄 영역으로 나누어 질 수 있다. 평탄 영역은 대부분 저주파 성분으로 이루어져 있지만, 에지 영역에서는 고주파 성분이 주가 된다. 따라서, 각 영역에 따른 특성을 고려한 deinterlacing 방법이 효율적이라고 할 수 있다. 본 논문에서는 국부 영역의 분산을 사용하여 영상을 에지 영역과 평탄 영역으로 분리하고 분리된 에지 영역과 평탄 영역에 대하여 모듈화된 신경 회로망을 사용한 deinterlacing 방법을 제안한다. 제안 방법에서는 모듈화된 구조로 인해 각 영역의 신경회로망이 유사한 데이터들만을 집중적으로 학습할 수 있고 서로 다른 영역의 데이터들로 인한 학습방해가 적은 장점이 있다. 또한 신경 회로망의 입력으로 국부 평균을 제거한 값을 사용함으로써 화소의 국부 평균 밝기값의 변화로 인한 학습 성능 저하를 방지할 수 있다. 모의 실험에서 제안된 알고리즘은 기존 알고리즘들보다 개선된 성능을 보였다.

• 한국전자파학회논문지
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• 제24권5호
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• pp.541-548
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• 2013

본 논문에서는 상용 벡터 회로망 분석기를 사용하지 않고도, 신호 발생기, 벡터 전압 수신기, 방향성 결합기, 주파수 혼합기 등의 기본적인 초고주파 장비/소자를 활용하여 평가하고자 하는 초고주자 소자의 2-포트 산란 계수를 측정할 수 있는 시스템을 제안한다. 벡터 회로망 분석기를 대용할 수 있는 산란 계수 측정 시스템의 해석적 모델과 제작방법을 제시하고, 이를 1-포트와 2-포트 소자에 대하여 각각 적용한 산란 계수를 측정하여 구현된 시스템을 평가하였다. 평가 주파수 대역에 따라 비교적 낮은 대역에서는 단일 신호 발생기와 벡터 전압 수신기를 사용한 직접 수신법을, 높은 대역에서는 추가의 신호원과 주파수 혼합기를 사용하여 신호를 하향 복조하는 헤테로다인 방식을 사용하여 산란 계수를 결정짓는 벡터 전압을 수신하였다. 이들 각각의 수신 방법으로 UHF와 X 대역 초고주파 소자의 2-포트 산란 계수를 평가하였고, 그 유효성을 상용 벡터 회로망 분석기로 검증하였다.

• 한국통신학회논문지
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• 제36권4C호
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• pp.241-253
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• 2011

본 논문에서는 릴레이 기반 무선 통신 환경에서 기존의 CFNC (Complex Field Network Coding) 기법 적용 시 발생하는 문제점들을 개선하는 방안을 제시한다. CFNC 기법은 간단한 복소 덧셈 및 뺄셈 연산을 통해 상 하향 링크 신호 교환에 요구되는 시간 구간을 최소화함으로써 전송 효율을 극대화하는 장점을 가진다. 그러나, 기존의 CFNC 기법은 릴레이에서의 ML (Maximum Likelihood) 판정 과정에서 큰 폭의 성능 열화가 발생하는 단점이 있다. 또한, CFNC 기법 적용 시 릴레이의 수신 신호에 다중 주파수 오프셋이 발생함에 따라 릴레이의 미세 주파수 오프셋 추정 성능이 열화 되는 한편, 주파수 오프셋 보상 이후에도 잔류 주파수 오프셋으로 인한 성능 열화가 발생하는 문제점이 있다. 따라서 본 논문에서는 상향 링크의 송신 다이버시티를 이용함으로써 정확도를 개선 가능한 새로운 ML 판정 기법 및 다중 주파수 오프셋 환경에서 적용 가능한 새로운 미세 주파수 오프셋 추정, 보상 기법을 제안한다. 다양한 환경에서의 컴퓨터 모의실험을 통해 제안된 기법들이 CFNC 기법 적용 시 발생하는 문제점들을 효과적으로 개선 가능함을 입증한다.