• 한국통신학회논문지
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• 제25권9A호
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• pp.1290-1298
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• 2000

터보 부호의 복호기는 각 복호 단계마다 순방향과 역방향의 메트릭을 계산하여 복호할 비트의 잉여 정보를 추출하여 다음 복호 단계에서 이 정보를 이용하는 반복 복호 기술이다. 터보 부호는 인터리버의 크기가 크고 반복 복호가 충분히 수행되었을 때 BER의 관점에서 Shannon Limit에 근접하는 우수한 성능을 보였다. 그러나 많은 연산량에 따른 복잡도의 증가와 인터리버와 반복 복호에 따른 지연과 실시간 처리의 어려움이라는 문제점을 안고 있다. 본 논문에서는 터보 부호의 복호 알고리즘으로 사용되고 있는 MAP(maximum a posteriori) 알고리즘과 이의 성능을 결정하는 요소를 분석한다. MAP알고리즘은 모든 인접 비트들과 수신 심벌들 사이의 상태와 천이 확률을 통해 연성 결정값을 결정하여 반복 복호 동작을 수행한다. 그러므로 MAP알고리즘의 성능 향상을 위해서는 인접한 수신 심볼들의 신뢰성을 보장해 주어야만 한다. 하지만 MAP 알고리즘 자체에서는 이를 위한 어떠한 동작도 해줄 수가 없기 때문에 추가적인 알고리즘이 필요하디는 결론을 얻을 수 있으며 반복 복호 동작을 줄일수 있게된다. 따라서 수신된 심볼에 대하여 좀 더 신뢰성을 있는 정보를 MAP 알고리즘의 입력으로 주기 위해 Robust 등화기법을 적용하여 MAP 알고리즘과 터보 부호의 성능을 비가우시안 채널 환경에서 분석한다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 춘계학술대회
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• pp.65-70
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• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

• 한국해양환경ㆍ에너지학회지
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• 제6권4호
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• pp.3-12
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• 2003

지속적인 산업화와 도시화에 따른 에너지 수요의 급증으로 인해 원유와 석유제품의 해양수송이 점점 증가하고 있다. 우리나라의 경우 국내의 유류 수요를 맞추기 위해서는 매일 30만톤급의 대형 유조선이 입항해야 하기 때문에 대형 유류오염 사고에 노출되어 있다 해양 유류오염사고의 가능성을 줄이기 위해 부단한 노력에도 불구하고 회복하기 어려운 유출 사고는 인간의 실수, 악천후 또는 복합적인 이유로 일어나게 된다. 따라서 적절한 대응시스템으로 지역방제계획을 세워 최악의 경우에 대비하고 해양환경과 연안자원을 보호해야만 한다. 특히 보호의 우선순위를 명확히 하고 현장 방제전략을 세움으로써 유출과 방제의 노력이 환경에 미치는 영향을 줄이기 요구되는 방제정보지도에 초점을 맞추었다. 본 논문에서는 기름에 대한 민감도의 정의와 개발한 소프트웨어의 주요특짚과 함께 방제정보지도를 간략히 소개한다.

• 한국산학기술학회논문지
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• 제11권1호
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• pp.141-150
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• 2010

본 논문은 전력선 통신 채널에서 터보 부호와 OFDM 시스템의 성능을 분석하고 시뮬레이션 하였다. 전력선통신 시스템은 최악의 환경에서 동작되기 때문에 터보 부호는 전송 데이터의 신뢰성을 보장하기 위해서 사용되었다. 시뮬레이션의 성능은 비트 오류 확률로써 표현하였다. 터보 복호 알고리즘으로써 MAP과 Max-Log MAP 알고리즘, 그리고 SOVA를 선택하였고, 이것들의 성능을 비교하였다. 시뮬레이션 결과로부터, Max-Log MAP 알고리즘이 성능과 복잡도면에서 유망하다는 것이 입증되었다. 그리고 터보 부호기의 인터리버 길이가 100에서 5000으로 변할 때와 반복 횟수가 2번에서 8번으로 증가할 때, 각 각 3dB증가하였음을 알 수 있다. 본 논문에서의 결과는 OFDM를 기반으로 하는 전력선 통신 시스템에 적용될 수 있음을 보여준다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.295-298
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• 2003

In this paper, a novel maximum a posterion (MAP) estimation for the channel decoding of H.264 codes in the presence of transmission error is presented. Arithmetic codes with a forbidden symbol and trellis search techniques are employed in order to estimate the best transmitted. And, there has been growing interest of communication, the research about transmission of exact data is increasing. Unlike the case of voice transmission, noise has a fatal effect on the image transmission. The reason is that video coding standards have used the variable length coding. So, only one bit error affects the all video data compressed before resynchronization. For reasons of that, channel needs the channel codec, which is robust to channel error. But, usual channel decoder corrects the error only by channel error probability. So, designing source codec and channel codec, Instead of separating them, it is tried to combine them jointly. And many researches used the information of source redundancy In received data. But, these methods do not match to the video coding standards, because video ceding standards use not only one symbol but also many symbols in same data sequence. In this thesis, We try to design combined source-channel codec that is compatible with video coding standards. This MAP decoder is proposed by adding semantic structure and semantic constraint of video coding standards to the method using redundancy of the MAP decoders proposed previously. Then, We get the better performance than usual channel coder's.

• 한국지진공학회논문집
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• 제19권3호
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• pp.93-102
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• 2015

This study evaluates collapse probabilities of structures which are designed according to a domestic seismic design code, KBC2009. In evaluating their collapse probabilities, to do this, probabilistic distribution models for seismic hazard and structural capacity are required. In this paper, eight major cities in Korea are selected and the demand probabilistic distribution of each city is obtained from the uniform seismic hazard. The probabilistic distribution for the structural capacity is assumed to follow a underlying design philosophy implicitly defined in ASCE 7-10. With the assumptions, the structural collapse probability in 50 years is evaluated based on the concept of a risk integral. This paper then defines an mean value of the collapse probabilities in 50 years of the selected major cities as the target risk. Risk-targeted spectral accelerations are finally suggested by modifying a current mapped spectral acceleration to meet the target risk.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.71-76
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• 2003

The purpose of this study is the development, application and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence, For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1988년도 가을 학술발표회 논문집
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• pp.7-12
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• 1988

This study presents rational methods for probability-based estimates of basic design wind speeds in Korea and develops a risk-bases nation-wide map of design wind speeds. The paper examines the fitting of the Type-I extreme model to maximum yearly non-typhoon wind data from long-term records based on the conventional method and to maximum monthly nod-typhoon wind data from short-term records following Grigorin's approach. The paper also reviews the applicability of the method using short records of about 5 years. The basic design wind speeds for typhoon and non-typhoon wind at a station are made to be obtained from a mixed model which is given as a product of typhoon and non-typhoon extreme wind distributions. A practical method which is based on the fitting of the Type I model to records or typhoon and non-typhoon mixed wind data at a station is also preposed in this study.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.398-398
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• 2000

Since there is a blind zone in driver's view around the excavator, industrial accidents between the equipment and the workers within the zone have been occurred frequently. The purpose of this paper is to develop a obstacle recognition system which can prevent such an accident by providing the driver with the information on direction and distance of the obstacle within the blind zone. We designed the ultrasonic sensor based obstacle recognition system which consists of sensor arrays and a control unit connected via CAN(controller area network). The Cross-correlation technique and histogramic probability distribution method are used as a reliable obstacle detection algorithms to remove the environmental noise. The experimental results using a real excavator show the effectiveness of the system.

• 로봇학회논문지
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• 제12권4호
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• pp.432-440
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• 2017

In this paper, we propose a jellyfish distribution recognition and monitoring system using a UAV (unmanned aerial vehicle). The UAV was designed to satisfy the requirements for flight in ocean environment. The target jellyfish, Aurelia aurita, is recognized through convolutional neural network and its distribution is calculated. The modified deep neural network architecture has been developed to have reliable recognition accuracy and fast operation speed. Recognition speed is about 400 times faster than GoogLeNet by using a lightweight network architecture. We also introduce the method for selecting candidates to be used as inputs to the proposed network. The recognition accuracy of the jellyfish is improved by removing the probability value of the meaningless class among the probability vectors of the evaluated input image and re-evaluating it by normalization. The jellyfish distribution is calculated based on the unit jellyfish image recognized. The distribution level is defined by using the novelty concept of the distribution map buffer.