• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.761-764
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• 2000

This paper presents a Fuzzy Neural Network (FNN) system to decide whether or not the right information of lanes can be extracted from gray-level images of road scene. The decision of noisy level of input images has been required because much noises usually deteriorates the performance of feature detection based on image processing and lead to erroneous results. As input parameters to FNN, eight noisiness indexes are constructed from a cumulative distribution function (CDF) and proved the indexes being classifiers of images as the good and the bad corrupted by sources of noise by correlation analysis between input images and the indexes. Considering real-time processing and discrimination efficiency, the proposed FNN is structured by eight input parameters, three fuzzy variables and single output. We conduct much experiments and show that our system has comparable performance in terms of false-positive rates.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.303-305
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• 2015

본 논문에서는 나카가미-m 페이딩 채널 환경을 가진 무선 중계 네트워크에서 reactive 누적분포함수(cumulative distribution function) 기반 중계기 선택 기법을 제안한다. 제안된 기법은 수신 신호대잡음비(signal-to-noise ratio)의 누적분포함수 값에 따라 중계기를 선택한다. 본 논문에서는 제안한 기법의 불능 확률(outage probability)과 다이버시티 차수(diversity order)를 분석한다. 제안된 기법이 얻을 수 있는 다이버시티 차수는 중계기의 개수와 페이딩 파라미터에 의해 결정되며 최대 다이버시티(full diversity)를 얻음을 볼 수 있다. 그리고 모의 실험에서는 분석된 불능 확률 및 다이버시티 차수가 정확하게 일치하는 것을 확인한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.368-370
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• 2012

본 논문에서는 이중 홉 무선 네트워크에서 누적분포함수(cumulative distribution function) 기반 중계기 선택 기법을 제안한다. 제안된 기법은 수신 신호대잡음비(signal-to-noise ratio)의 누적분포함수 값에 따라 중계기를 선택한다. 본 논문에서는 제안한 기법의 중계기 공정성에 대한 분석을 통해 제안된 기법이 엄격하게 공정성을 달성할 수 있음을 보인다. 그리고 모의 실험에서는 round-robin 기법과 기회적 중계 기법을 제안된 기법과 총 타임 슬롯에 대한 각 중계기별 타임 슬롯 분배율, 평균 공정성, 불능확률 비교를 통해 제안된 기법이 엄격하게 공정성을 달성하는 것과, 기회적 중계 기법과 거의 동일한 기울기로 불능확률이 떨어지는 것을 확인한다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.311-312
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• 2006

In this paper, a real-time stereoscopic image conversion method using a single frame from a 2-D image is proposed. If original image is too much dark, it is difficult to create correct luminance value. So stereoscopic image is generated after applied image enhancement algorithm to original image. The Stereoscopic image is generated by creating depth map using vertical position information and parallax processing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.225-228
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• 2009

본 논문에서는 인접블록간의 움직임 유사도를 이용하여 불필요한 후보블록을 보다 빠르게 제거하는 PDE기반의 고속 블록매칭 알고리즘을 제안한다. 제안한 방법은 기존의 방법보다 불필요한 계수를 효율적으로 제거하기 위하여 인접 블록간의 영상의 유사성에 기초하여 네 개의 인접 매크로블록 가운데 최대 복잡도를 가지는 서브블록의 누적 분포 함수(cumulative distribution function-CDF)와 서브블록별 복잡도가 집중되지 않도록 하기위하여 normalized스캔 방법에 사용하여 효율적으로 계산량을 감소하였다. 제안한 알고리즘은 화질의 저하 없이 기존의 PDE 알고리즘에 비해 55% 이상의 계산량을 줄였으며, MPEG-2 및 MPEG-4 AVC를 이용하는 비디오 압축 응용분야에 유용하게 사용될 수 있을 것이다.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.146-147
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• 2009

본 논문에서는 단일 프레임 내에서 인접한 매크로 블록 간의 움직임의 유사도를 이용한 개선된 PDE 알고리즘을 제안한다. 제안한 방법은 기존의 방법보다 불필요한 후보 블록을 효율적으로 제거하기 위하여 인접한 매크로블록간의 유사도를 고려하여 인접 4개의 매크로블록 가운데 서브 블록간 최대 복잡도를 가지는 서브블록의 CDF(cumulative distribution function)와 개선된 매칭스캔 방법을 이용하여 효율적으로 계산량을 줄였다. 제안한 알고리즘은 화질의 저하 없이 기존의 PDE 알고리즘에 비해 55% 이상의 계산량을 줄였으며, MPEG-2 및 MPEG-4 AVC를 이용하는 비디오 압축 응용분야에 유용하게 사용될 수 있을 것이다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.124-132
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• 2011

In a modern electronic warfare, radar signal environments become more denser and complex. Therefor the capability of reliable signal analysis techniques is required for ES(Electronic warfare Support) system to identify and analysis individual emitter signals from received signals. In this paper, we propose the new signal grouping algorithm to ensure the reliable signal analysis and to reduce the cost of the signal processing steps in the ES. The proposed grouping algorithm uses KDE(Kernel Density Estimator) and its CDF(Cumulative Distribution Function) to compose windows considering the statistical distribution characteristics based on the radar frequency modulation type. Simulation results show the good performance of the proposed technique in the signal grouping.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1186-1192
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• 2008

The reliability of gas turbine engine blades was studied. Yield strength, Young’s modulus, engine speed and gas temperature were considered as statistically independent random variables. The failure probability was calculated using five different methods. Advanced Mean Value Method was the most efficient without significant loss in accuracy. When random variables were assumed to have normal, lognormal and Weibull distributions with the same means and standard deviations, the CDF of limit state equation did not change significantly with the distribution functions of random variables. The normalized sensitivity of failure probability with respect to standard deviations of random variables was the largest with gas temperature. The effect of means and standard deviations of random variables was studied. The increase in the mean of gas temperature and the standard deviation of engine speed increased the failure probability the most significantly.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.3
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• pp.193-202
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• 2014

This paper presents a new method of sampling the climatic data for infrared signature analysis. Historical hourly data from a stationary marine buoy of KMA(Korean Meteorological Administration) are used to select a small number of sample points (N=100) to adequately cover the range of statistics(PDF, CDF) displayed by the original data set (S=56,670). The method uses a coarse bin to subdivide the variable space ($3^5$=243 bins) to make sample points cover the original data range, and a single-point ranking system to select individual points so that uniform coverage (1/N = 0.01) is obtained for each variable. The principal component analysis is used to calculate a joint probability of the coupled climatic variables. The selected sample data show good agreement to the original data set in statistical distribution and they will be used for statistical analysis of infrared signature and susceptibility of naval ships.