• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2002년도 종합학술발표회 논문집 Vol.12 No.1
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• pp.44-48
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• 2002

This paper describes an adaptive signal processing of digital receiver with DDC(Digital Down Convertor), DDC is implemented by using NCO(Numerically Controlled Oscillator), digital low pass filter. for the passband sampling, we present the results of digital receiver simulation with DDC. We confirm that the low IP signal is converted to zero IF by DDC. DOA(Direction Of Arrival) estimation technique using MUSIC(Multiple SIgnal Classification) algorithm with high resolution is presented. We Cow that an accurate resolution of DOA depends on the input sampling number.

• 대한기계학회논문집A
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• 제27권8호
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• pp.1251-1258
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• 2003

This paper presents a nonlinear robust approach to the slip control problem for a torque converter bypass clutch in a passenger car. The proposed nonlinear robust controller builds upon only the measurements avail-able from inexpensive sensors that are already installed in passenger cars for control. The issue of torque estimation problems for the implementation of the proposed controller is addressed. The stability of the internal dynamics is investigated, upon which a nonlinear robust controller is designed using input-output feedback linearization and Lyapunov redesign technique. The performance of the designed controller is validated by simulation studies.

• 신재생에너지
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• 제10권2호
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• 대한전기학회논문지
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• 제38권10호
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• pp.795-804
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• 1989

A parallel analog-to digital converter with neuron-like elements is designed and optically implemented. Its operation principle is based on the simultaneous estimation of bit values for a given analog input. The architecture of the proposed analog-to-digital converter is simpler than that of an earlier one designed by the energy minimization technique, and its digital output is independent of the initial state. Mixed binary-to-full binary converters are also designed by using out analog-to-digital converters as basic computing elements. These converters have simple structures and fast conversion times compared with earlier ones.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.378-383
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• 2000

The daily streamflow in the Yalu watershed located in the north-estern part of China was simulated by the DAWAST model. The parameters of model were calibrated by optimization technique with the input data of daily rainfall and pan evaporation occurred from 1997 to 1998, and they were Umax of 404mm, Lmax of 39mm, FC of 104mm, CP of 0.018, and CE of 0.003, respectively. Model verification tests were carried out with a data of 1996, and the results were generally satisfactory. Root mean square error was 0.3mm and Percent error in volume was 9.7%, and Correlation coefficient was 0.941.

• 한국전자통신학회논문지
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• 제6권5호
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• pp.637-642
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• 2011

본 논문에서는 움직임 객체 검출 기법의 성능을 향상시키기 위하여 소실점과 움직임 객체간의 거리를 추정하는 기법을 제안한다. 이를 위하여 먼저, 주어진 입력 영상에 대하여 하프변환을 이용하여 소실점을 추정하고, 이를 바탕으로 소실점과 움직임 객체간의 거리를 추출한다. 얻어진 거리 정보는 움직임 객체 추출에 효과적으로 사용된다. 모의실험에서 제안된 기법에 대한 모의실험 결과를 제시하였으며, 객체단위의 거리추정을 객체 추정에 활용할 수 있음 확인할 수 있었다.

• 한국환경과학회지
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• 제6권3호
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• pp.205-211
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• 1997

For the prediction of multi-site rainfall with radar data and ground meteorological data, a rainfall prediction model was proposed, which uses the neural network theory, a kind of artifical Intelligence technique. The Input layer of the prediction model was constructed with current ground meteorological data, their variation, moving vectors of rain- fall field and digital terrain of the measuring site, and the output layer was constructed with the predicted rainfall up to 3 hours. In the application of the prediction model to the Pyungchang river basin, the learning results of neural network prediction model showed more Improved results than the parameter estimation results of an existing physically based model. And the proposed model comparisonally well predicted the time distribution of ralnfall.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.889-893
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• 2000

In this paper, a method to detect lanes and obstacles from the images captured by a CCD camera fitted in an automobile is proposed, and a new terminology “Moving Window” is defined. Processing the input dynamic images in real time can cause quite a few constraints in terms of hardware. In order to overcome these problems and detect lanes and obstacles in real time using the images, the optimal size of “Moving Window” is determined, based upon road conditions and automobile states. The real time detection is made possible through the technique. For each image frame, the moving window is moved in a predicted direction, the accuracy of which is improved by the Kalman filter estimation. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of freeway driving.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제53권4호
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• pp.200-207
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• 2004

This paper presents a simple and fast delay metric RC-class interconnects under saturated ramp inputs. The RC delay metric under saturated ramp inputs, called FDM(Fast Delay Metric), can estimate delay times at an arbitrary node using a simple closed-form expression and is extended from delay metric under step input easily As compared with similar techniques proposed in previous researches, it is shown that the FDM technique complexity for a similar accuracy. As the number of circuit nodes increases, there will be a significant difference in estimation times of RC delay between the previous techniques based on two circuit moments and the FDM which do not depend on circuit moments.

• Smart Structures and Systems
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• 제12권2호
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• pp.121-136
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• 2013

This study proposes an innovative control approach to suppress the responses of a beam structural system under moving forces. The proposed control algorithm is a synthesis of the adaptive input estimation method (AIEM) and linear quadratic Gaussian (LQG) controller. Using the synthesis algorithm the moving forces can be estimated using AIEM while the LQG controller offers proper control forces to effectively suppress the beam structural system responses. Active control numerical simulations of the beam structural system are performed to evaluate the feasibility and effectiveness of the proposed control technique. The numerical simulation results show that the proposed method has more robust active control performance than the conventional LQG method.