• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.124-127
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• 2000

This paper describes the algorithm for more fast tracking by compensation of the staring angle of antenna to receive the satellite signal changed by the mobile vehicle direction. The staring angle is compensated by signal processing from the electronic compass which is called VECTOR2X, and a left-right tracking method. Especially, when mobile vehicle is turning with high speed, it is observed a result which has more fast tracking time by using angle tracking technique compensated by electronic compass than one by only left right tracking method.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.343-346
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• 2002

This paper presents an advanced auto focus camera system using the adaptive zoom tracking method. The proposed system can achieve an accurate zoom tracking with significantly reduced system memory.

• Korean Journal of Applied Biomechanics
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• v.17 no.1
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• pp.81-90
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• 2007

The effort identifying positioning information of the moving object in real time has been a issue not only in sport biomechanics but also other academic areas. In order to solve this issue, this study tried to track the movement of a pitched ball that might provide an easier prediction because of a clear focus and simple movement of the object. Machine learning has been leading the research of extracting information from continuous images such as object tracking. Though the rule-based methods in artificial intelligence prevailed for decades, it has evolved into the methods of statistical approach that finds the maximum a posterior location in the image. The development of machine learning, accompanied by the development of recording technology and computational power of computer, made it possible to extract the trajectory of pitched baseball from recorded images. We present a method of baseball tracking, based on object tracking methods in machine learning. We introduce three state-of-the-art researches regarding the object tracking and show how we can combine these researches to yield a novel engine that finds trajectory from continuous pitching images. The first research is about mean shift method which finds the mode of a supposed continuous distribution from a set of data. The second research is about the research that explains how we can find the mode and object region effectively when we are given the previous image's location of object and the region. The third is about the research of representing data into features that we can deal with. From those features, we can establish a distribution to generate a set of data for mean shift. In this paper, we combine three works to track baseball's location in the continuous image frames. From the information of locations from two sets of images, we can reconstruct the real 3-D trajectory of pitched ball. We show how this works in real pitching images.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.55-62
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• 1999

In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. In this paper, to bring under robust ard accurate control of auto-equipnent systems which disturbance, parameter alteration of system, uncertainty ard so forth exist, neural network controller called dynamic neural processor(DNP) is designed. Also, the learning architecture to compute inverse kinematic coordinates transfonnations in the manirclator of auto-equipnent systems is developed ard the example that DNP can be used is explained The architocture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simllations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.he DNP.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.12
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• pp.55-61
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• 2009

Machining systems have been evolved to produce more detailed products of high added value. This has been possible, in large part, due to the development of highly accurate multi-axis CNC machine tools. The conventional CNC of machine tools has individual axis controllers to maximize tracking performance. On the other hand, cross-coupling controllers can be integrated into the conventional CNC to enhance contouring performance. For this multi-axis cross-coupling control system, it is necessary to automatically adjust the controller gains depending on operating conditions and/or other external conditions from an optimization perspective. This paper proposes automatic modeling of feed drive systems that minimizes the difference in behavior between the system model and the actual system. Based on the modeling, an integrated auto-tuning method is also proposed to improve both tracking and contouring accuracy of a 3-axis cross-coupling control system as well as users' convenience. The proposed methods are evaluated by both simulation and experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1574-1580
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• 2008

In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. Also, the learning architecture to compute inverse kinematic coordinates transformations in the Plants of auto-equipment systems is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.121-125
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• 2007

In this paper, a planar active retrodirective four-element array with subharmonic phase conjugation mixers based on anti-parallel diode pairs (APDPs) is designed, and its application in the auto-tracking duplex communication link is presented. As compared to previous phase conjugation mixers using twice RF frequency for LO frequency, the proposed conjugation mixers need only half RF frequency so that it can be easily applied for millimeter-wave applications. The proposed architecture, which conventionally performs the function of the transmission of an incident signal back in the direction of its source, is modified in order to include a receive function. Experimental verification of these architectures is performed at 1GHz and the results from the prototypes are compared with a theoretical model.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1799-1802
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• 2007

In the constructed auto-stereoscopic display system for one observer. 1.stereoscopic images displayed on a special LCD are made on a large concave mirror. 2.The view-zone limiting aperture is set between the projection lens and the concave mirror. 3.The real image of the aperture is made at the observer's eye position by the concave mirror. 4.The observer's eye-position tracking of the view-zone is realized. 5.At same time, stereoscopic image changes automatically according to the eye position of the observer.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.84-86
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• 2001

A new navigation method is developed and implemented for mobile robot. The mobile robot navigation problem has traditionally been decomposed into the path planning and path following. Unlike tracking-based system, which minimize intercept time and moved mobile robot distance for optimal rendezvous point selection. To research of random moving object uses algorithm of Adaptive Control using Auto-regressive Model. A fine motion tracking object's trajectory is predicted of Auto-regressive Algorithm. Thus, the mobile robot can travel faster than the target wi thin the robot's workspace. The can select optimal rendezvous point of various intercept time.

• Journal of Convergence Society for SMB
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• v.4 no.1
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• pp.31-39
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• 2014

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedback were changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control. We also applied to reference tracking problem with the designed auto-tuning scheme.