• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.54-57
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• 2000

In vector quantization (VQ), mean squared difference (MSD) is a widely used distance measure between vectors. But the distance between the means of each vector elements appears as a dominant quantity in MSD. In the case of image vectors, the coincidence of edge patterns is also important when the human visual system (HVS) is considered. Therefore, we propose a new distance measure that uses the variance of differences to encode vectors and to design codebooks. It can choose more proper codewords to reduce edge degradations and make a useful codebook, which has lots of various edge codewords in place of redundant shades.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2374-2376
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• 2000

In this paper, we propose an indirect vector control method using Adaptive Neuro-Fuzzy Inference System (ANFIS) parameter estimator. It estimates the rotor time constant when the indirect vector control of induction motor is applied. We use the stator current error that is difference between the current command and estimated current calculated from terminal voltage and current. And two induced current estimate equations are used in training ANFIS.The estimator is trained by the hybrid learning algorithm. Simulation results shows good performance under load disturbance and motor parameter variations.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.1044-1050
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• 2001

This paper presents firstly the method of Euler angle matching designing the transfer alignment using the attitude matching. In this method, the observation directly uses Euler angle difference between MINS and SINS so it needs to describe the rotation vector error to the Euler angle error. The rotation vector error related to the Euler angle error is derive from the direction cosine matrix error equation. The feasibility of the Kalman filter designed for the transfer alignment by Euler angle matching is analyzed by the alignment error results with respect to the roll angle the pitch angle, and the yaw angle matching.

• Proceedings of the KIEE Conference
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• 1983.07a
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• pp.135-138
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• 1983

This paper studies a variable structure adaptive model following control system which can control a plant in which the parameters of the controlled plant can not be estimated because they vary with time and in which the controlled plant has noise. The values of the feedback gain matrices for given states are obtained the equivalent control law, and the adaptive controller has been designed using the adaptive mechanism which switches the matrices. The adaptive controller minimizes the state error vector, that is, the difference between the state vector of the model and the state vector of the controlled plant. A controlled plant which has time varying parameters, a controlled plant which has only noise, and a controlled plant which has both have been controlled by the designed adaptive controller. The continuous single input-output system has been analysed by computer. This control system may be used to control practical systems by the addition of a microcomputer.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.4
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• pp.143-148
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• 2002

Up to now, DC-biased magnetic properties have been measured in one dimension (scalar). However, scalar magnetic properties are insufficient to clarify DC-biased magnetic properties because scalar magnetic properties can only impossibly consider the phase difference between the magnetic flux density B vector and the magnetic field strength H vector. Thus the magnetic field strength H and magnetic flux density B in magnetic materials must be directly measured as a vector quantity (two-dimensional). This paper presents measurement system to clarify the two-dimensional DC-biased magnetic properties.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2161-2163
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• 2003

This Paper presents a vector control method for the parallel-connected motor drive system. The new estimation scheme of rotor flux position is presented to reduce sensitivity due to load difference between the motors. To confirm the validity of the proposed control method, we compare a simulation result of the proposed control method with that of the conventional indirect vector control method. The simulation results show that the proposed control method is more effective step change in load torque.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.77-85
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• 2004

This paper proposes a multi-level vector error diffusion method using 64 primary colors to improve color impulse artifact in bright region. Vector error diffusion method causes color impulse artifact in bright region because we only use the Euclidean distance measure in quantization process. In order to reduce this artifact, the proposed method divides input color into chromatic color and achromatic color according to chroma value. In the case of chromatic color, input color is classified into bright region, middle bright region, and dark region according to lightness value. N candidate primary color is organized using lightness difference between input vector and 60 chromatic primary color vector in the case of bright region. Then, primary color with minimum vector norm between input vector and N candidate primary color in addition to 4 achromatic primary colors is selected as output color. As a result of experiments, the proposed method showed visually pleasing halftone output.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.98-106
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• 2016

Remote sensing is an efficient technology for observing and monitoring the land surfaces inaccessible to humans. This research proposes a methodology for improving the accuracy of the land cover classification using the Landsat-8 operational land imager(OLI) image. The proposed methodology consists of the following steps. First, the normalized difference vegetation index(NDVI) and normalized difference water index(NDWI) images are generated from the given Landsat-8 OLI image. Then, a new image is generated by adding both NDVI and NDWI images to the original Landsat-8 OLI image using the layer-stacking method. Finally, the maximum likelihood classification(MLC), and support vector machine(SVM) methods are separately applied to the original Landsat-8 OLI image and new image to identify the five classes namely water, forest, cropland, bare soil, and artificial structure. The comparison of the results shows that the utilization of the layer-stacking method improves the accuracy of the land cover classification by 8% for the MLC method and by 1.6% for the SVM method. This research proposes a methodology for improving the accuracy of the land cover classification by using the layer-stacking method.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1308-1316
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• 2018

Accurate tuning of parameter is very important in vector-controlled induction motor. Among the parameters of induction motor, detuning of rotor resistance used in controller design deteriorates drive performance. This paper presents a novel rotor resistance estimation strategy using slip angular velocity in vector-controlled induction motor drives. The slip angular velocity can be calculated by two methods. Firstly, it can be induced from the rotor voltage equation. Secondly, it can be induced from the difference between synchronous angular velocity and rotor angular velocity. The first method includes the rotor resistance, while the second method dose not include this parameter. From this fact, the rotor resistance can be identified by comparing the slip angular velocities in the two methods. In the tuned states of the rotor resistance, performances of flux estimator and speed drive are discussed. The simulation and experimental results are given to verify the validity of the proposed method in various situations.