• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.936-941
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• 2004

An Optimal Feedforward Integral Variable Structure or FIVSC approach for an electrohydraulic position servo control system is presented in this paper. The FIVSC algorithm combines feedforward strategy and integral in the conventional Variable Structure Control (VSC) and calculating the control function to guarantee the existence of a sliding mode. Furthermore, the chattering in the control signal is suppressed by replacing the sign function in the control function with a smoothing function. The simulation results illustrate that the purposed approach gives a significant improvement on the tracking performances when compared with some existing control methods, like the IVSC and MIVSC strategies. Simulation results illustrate that the purposed approach can achieve a zero steady state error for ramp input and has an optimal motion with respect to a quadratic performance index. Moreover, Its can achieve accurate servo tracking in the presence of plant parameter variation and external load disturbances.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.337-345
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• 2009

The dependence of numerous systems on electronic devices is causing rapidly increasing concern over fault tolerance because of safety issues of safety critical system. As an example, a vehicle with electronics-controlled system such as x-by-wire systems, which are replacing rigid mechanical components with dynamically configurable electronic elements, should be fault￢tolerant because a devastating failure could arise without warning. Fault-tolerant systems have been studied in detail, mainly in the field of aeronautics. As an alternative to solve these problems, this paper presents the fuzzy hybrid redundancy system that can remove most erroneous faults with fuzzy fault detection algorithm. In addition, several numerical simulation results are given where the fuzzy hybrid redundancy outperforms with general voting method.

• Journal of Information Technology Applications and Management
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• v.14 no.1
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• pp.137-144
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• 2007

In this paper, we propose a rotation resistant robust logo embedding watermarking technique. Geometric manipulations make the detection process very complex and difficult. Watermark embedding in the normalized image directly suffers from smoothing effect due to the interpolation during the image normalization. This can be avoided by estimating the transform parameters using image normalization angle and moments, instead of embedding in the normalized image. Conventional rotation resistant schemes that use full frame transform. In this paper we adopt DCT and calculate masking using a spatio-frequency localization of the $8{\times}8$ block DCT coefficients. Experimental results show that the proposed algorithm is robust against rotation process.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2001.11b
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• pp.129-133
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• 2001

영상에 포함된 잡음은 화질 및 영상의 압축효율을 저하시킨다. 최근 들어, 영상의 에지 성분을 효율적으로 고려하면서 잡음을 제거하기 위하여 다양한 비정적(nonstationary) 영상 모델에 근거한 잡음제거 알고리즘이 제안되어 왔다. 하지만, 기존의 비정적 영상모델에서는 연산량의 부담을 덜기 위하여 각 화소들 사이에 상관관계(correlation)가 없다는 가정을 하고 있어 영상의 미세한 정보들이 필터링에 의하여 훼손된다. 본 논문에서는 영상의 비정적 상관관계를 고려한 적응적 잡음제거 알고리즘을 제시한다. 영상신호는 비정적 평균을 가진다고 가정되며, 또한 각기 다른 정적(stationary) 상관관계를 가지는 부분 영상으로 분리된다고 가정된다. 제안된 영상 모델에서의 공분산(co-variance) 행렬의 특수한 구조를 이용하여 계산적으로 효율적인 FFT에 기반한 선형 minimum mean square error 필터를 유도한다. 제안된 영상 모델의 정당성 및 알고리즘의 효율성을 제시한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.679-683
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• 2005

The technique which connects Generalized Regression Neural Networks Model(GRNNM) with Genetic Algorithm (CA) is used to derive rating curve in the river basin. GRNNM architecture consists of 4 layers ; input, hidden, summation and output layer. GA method is applied to estimate the optimal smoothing factor when GRNNM is trained. The derivation of rating curve using GRNNM is considered different kinds of hydraulic characteristics such as water stage, area and mean velocity and is applied two stage stations; Sunsan and Jungam. Furthermore, it is compared with conventional curve-fitting method. Through the training and validation performance, the results show that GRNNM is much superior as compared to the conventional curve-fitting method.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.900-904
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• 1991

In this paper, our study for the recognition of Hand-written Korean characters, Arabic numbers and alphabets by neural netwoks. This System extracts feature of character by using the MESH feature point of handwritten character, Arabic numbers and alphabets. To reduce the input image data, features are extracted from each input images. A MLP(multi-layer perceptron) with one hidden layer was trained with a modified BEP(back error propagation) algorithm. This method extracts feature sets of the characters directly from the scanner and can enhance computation speed without using the special preprocesses such as size normalization, smoothing, and thinning.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.436-438
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• 2002

인터넷 기술이 반전함에 따라서 인터넷을 통한 서비스에 대한 관심도가 증가되고 있다. 특히 멀티미디어 서비스인 경우 QoS(Quality of Service)를 보장해야 만다. 그런데 제한된 대역폭 내에서 전송량이 급격히 증가하는 경우 네트워크 자원의 이용도와 서비스의 품질에 큰 영향을 준다. 이에 스무딩 기법은 가변 비트율(VBR : Variable Bit Rate)을 가진 비디오 스트림(Stream)을 전송할 때 네트워크 자원의 이용도와 서비스의 품질 저하를 막기 위해 전송률(Transmission rate)을 일정하게 유지시키는 기법으로 서버와 네트워크 사이의 중간노드에서 수행된다. 본 논문에서 스무딩 알고리즘을 프레임 단위로 저리할 경우 해당자원의 과부하가 탄생하므로 이를 개선한 스무딩 알고리즘을 제안하고, 기존 스무딩 알고리즘의 시간 복잡도와 성능을 중심으로 비교 분석하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2271-2282
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• 2006

This paper is concerned with simulation issues arising in the PDE-based image restoration such as the total variation minimization(TVM) and its generalizations. In particular, we study the issues of staircasing and excessive dissipation of TVM-like smoothing operators. A strategy of scaling the algebraic system and a non-convex minimization are considered respectively for anti-staircasing and anti-diffusion. Furthermore, we introduce a variable constraint parameter to better preserve image edges. The resulting algorithm has been numerically verified to be efficient and reliable in denoising. Various numerical results are shown to confirm the claim.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.505-510
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• 2009

In this paper, building energy analysis and energy cost of power stand up and demand control over the power proposed to reduce power demand. Through analysis of the load power demand special day were able to apply the pattern. In addition, the existing rate of change of load forecasting to reduce the large errors were not previously available data. And daily schedules and special day for considering the exponential smoothing methods were used. Previous year's special day and the previous day due to the uncertainty of the load and the model components were considered. The maximum demand power control simulation using the fuzzy control of power does not exceed the contract. Through simulation, the benefits of the proposed energy-saving techniques were demonstrated.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.595-599
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• 2002

이미지 인식 분야에 있어서 전지 결재시 도장의 진위 문제라 은행 업무 또는 중요 서류에 있어서 도장의 진위 문제를 해결할 수 있는 방법이 필요하게 되었다. 따라서 본 논문에서는 평활화 방법과 ART1 알고리즘을 이용한 도장 이미지 인식 방법을 제안하였다. 제안된 방법은 임계값을 이용하여 도장 이미지를 이진화하고 이진화된 이미지에서 최빈수 평활화 방법을 이용하여 잡음을 제거하고 도장 영역을 추출하여 정규화 하였다. 도장 인식은 인공 신경망의 자율 학습 방법인 ART1 알고리즘을 적용 하였다. 실험 결과, 제안된 도장 인식 방법이 도장의 진위 문제에 적용할 수 있는 가능성을 확인하였다.