• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.799-803
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• 2007

In this paper, we propose a new fuzzy membership function for FSVM(Fuzzy Support Vector Machines). We apply a fuzzy membership to each input point of SVM and reformulate SVM into fuzzy SVM (FSVM) such that different input points can make different contributions to the learning of decision surface. The proposed method enhances the SVM in reducing the effect of outliers and noises in data points. This paper compares classification and estimated performance of SVM, FSVM(1), and FSVM(2) model that are getting into the spotlight in time series prediction.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.321-323
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• 1996

In this paper, it introduces a several circuit type of current-fed Full Bridge high frequence inverter with VVVF function. These inverter circuit presents various output control method according to on/off signal pattern of switches. also, It is certify that the accordance of characteristics is compared theoretical waveform with experimental results according to each signal pattern.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.2
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• pp.128-136
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• 1991

A neural network of multi layer perception type, learned by error back propagation learning rule, is generally used for the verification or clustering of similar type of patterns. When learning is completed, the network has a constant value of output depending on a pattern. This paper shows that the intensity of neuron's out put can be controlled by a function which intensifies the excitatory interconnection coefficients or the inhibitory one between neurons in output layer and those in hidden layer. In this paper the value of factor in the function to control the output is derived from the know values of the neural network after learning is completed And also this paper show that the amount of an increased neuron's output in output layer by arbitary value of the factor is derived. For the applications increased recognition performance of a pattern than has distortion is introduced and the output of partially damaged neurons are first managed and this paper shows that the reduced recognition performance can be recovered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.2
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• pp.392-400
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• 1997

In this paper we porposed WCHF-fSDF filter to obtain a roration and scale-invariant correlation output. WCHF-fSDF filter is synthesized by each single CHF exttracted from scale-changed and wavelet tranformed imagesfor a refereence image as tranining images. The wavelet transform is defined as the correlation of an input image with a wavelet function. Therefore two 4f optical correlation systems are needed for pattern recognition using wavelet transform. We here include the wavelet function for the input image in the process of the proposed filter design and substitute the two 4f optical correlation system with a single 4f optical correlation system. The Performances of the proposed filter are compared with conventional CHF-SDF, POCHF-SDF filters through the computer simulation. The results of computer simulation show that the proposed filter has the rotation and scale-invariant correlation output and it has better performances than thoseof the conventioanl filters.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.387-389
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• 2009

본 논문에서는 다항식 기반 Radial Basis Function(RBF)신경 회로망을 설계하고 이를 패턴분류 문제에 적용하여 그 성능을 분석한다. 제안된 RBF 신경회로망은 입력층, 은닉층, 출력층으로 이루어진다. 입력층의 연결가중치는 1로서 입력층의 입력벡터는 그대로 은닉층으로 전달되고 은닉층은 FCM(Fuzzy C-means Clustering)방법을 통하여 뉴런의 출력 값으로 내보낸다. 은닉층과 출력층사이의 연결가중치는 상수, 선형식 또는 이차식으로 이루어지며 경사 하강법에 의해 학습되어진다. 네트워크의 최종 출력은 연결가중치와 은닉층 출력의 곱에 의한 퍼지추론의 결과로 얻어진다. 제안된 RBF 신경회로망은 여러 종류의 machine learning 데이터에 적용하여 패턴분류기로서의 성능을 평가받는다.

• Journal of Mechanical Science and Technology
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• v.17 no.7
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• pp.966-977
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• 2003

This paper investigates how intentional mistuning of bladed disks reduces their sensitivity to unintentional random mistuning. The class of intentionally mistuned disks considered here is limited, for cost reasons, to arrangements of two types of blades (A and B, say). A two-step procedure is then described to optimize the arrangement of these blades around the disk to reduce the effects of unintentional random mistuning. First, a pure optimization effort is undertaken to obtain the pattern (s) of the A and B blades that yields small/the smallest value of the largest amplitude of response to a given excitation in the absence of unintentional random mistuning using Genetic Algorithm. Then, in the second step, a qualitative/quantitative estimate of the sensitivity for the optimized intentionally mistuned bladed disks with respect to unintentional random mistuning is performed by analyzing their amplification factor, probability density function and passband/stopband structures. Examples of application with simple bladed disk models demonstrate the significant benefits of using this class of intentionally mistuned disks.

• Journal of Advanced Marine Engineering and Technology
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• v.15 no.3
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• pp.45-56
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• 1991

This paper describes characteristics of the flow pattern of the flow past a rectangular cylinder experimentally investigated. The width-to-length ratio of the section varried from 2 to4. For the statistical treatment, autocorrelation coefficient, probability density function and power spectral density function are obtained by the digital processing technic through on-line system with a hot wire anemometer. As a results, it was found that strong periodic coherent eddies structure is sustained to about 20H downstream from the cylinder. And nearer the cylinder in the wake, the number of turbulent eddies of a large scale coherent structure are comparatively much more dominant than that of a small scale one. By the analysis of power spectrum, It was cleared that there exists a certain range of the width to length ratio between 2.5 and 3 of which the flow pattern changes abruptly with a sudden discontinuity in Strouhal number.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.8
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• pp.1127-1136
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• 1995

In this paper, a morphological shape decomposition method is proposed for the purpose of pattern recognition and image compression. In the method, a structuring element that geometrical characteristics is more similar to the shape function is preselected. The shape is decomposed into the primitive elements corresponding to the structuring element. A gray scale image also is transformed into 8 bit plane images for the hierarchical reconstruction required in image communication systems. The shape in each bitplane is decomposed to the proposed method. Through the experiment. it is proved that the description error is reduced and the coding efficiency is improved.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.357-365
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• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.77-85
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• 2009

In this paper, the implementation of creative engineering robot with MCU platform is described. This robot, as a platform of robot system to be used as creative engineering education, has to satisfy restrictions in many aspects in order to study algorithm and apply for the processor based function and pattern recognition application. Considering many restrictions of the mobile platform for creative robot system, we made this robot autonomous by using efficiently the LINUX embedded system. And we choose Marvell Monahan processor(PXA320) as MCU flatform, and used CentOS5.2 as an embedded OS that has the function of robustness and optimality. For flexibility and modularity, the platform has expansion ports. The results of experiment are described to show the pattern matching of creative engineering mobile robot with LINUX programming environments.