• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.165-168
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• 2004

This paper propose a target tracker using phase correlation. The tracker consist of a pre-processing module, a translation estimation module based on phase correlation, a fine motion estimation module applied when confidence rate could not fulfill a threshold value and a reference image update module. The fine motion estimation module measure the shift, rotation and scale of input image compared to reference using Fourier-Mellin transform. Proposed tracker was tested its accuracy and robustness using some real indoor and outdoor image sequences.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.10
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• pp.438-444
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• 1986

The signal can be modeled as a linear combination of its past values and present and past values of a hypothetical input to system whose output is given signal. Using this model spectral estimation problem can be reduced to estimate the ARMA parameters. This paper presents recursive modified instrumental variable algorithm which can estimate AR and MA parameters. For more accurate estimation, overdetermined modified IV algorithm is also derived. Computer simulations are presented to illustrate the above methods.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.697-700
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• 2000

This paper introduces a new rotor position estimation algorithm for the SRM based on the magnetizing curves of aligned and unaligned rotor positions. The flux linkage is calculated by the measured data from phase voltage and phase current and the calculated data are used as the input of magnetizing profiles for rotor position detection. Each of the magnetizing profiles consisted of the methods using the neural network and fuzzy algorithm And also the optima phase is selected by phase selector. To demonstrate the promise of this approach the proposed rotor position estimation algorithms are verified by the experiment results or variable spee range.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.70-74
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• 1989

To track the target trajectory with maneuvers, unknown maneuvering inputs must be estimated. To do this the direct estimation algorithm using generalized least square technique is developed based on the procedure of failure detection and identification(FDI) theory. Through the simulation using maneuvering target scenario, tracking performance and efficiency of the algorithm developed here are investigated.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.785-787
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• 1999

In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.442-445
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• 1987

In this paper, a new ARMA spectrum estimation algorithm based on Circular Lattice filter is presented. Since APMA model is used in signal modeling, high-resolution spectrum can be obtained. And the computational burden is reduced by using Circular Lattice filter. By modifying the input estimation part of other proposed methods, we can get high-resolution spectrum with less computation and less memory compared with other Lattice methods. Some computer simulations are performed.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.87-87
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• 2000

In this paper, an integrated design of fault detection, diagnosis and reconfigurable control tot multi-input and multi-output system is proposed. It is based on the interacting multiple model estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural and/or parametric changes. This research focuses on the method to recover the performance of a system with failed actuators by switching plant models and controllers appropriately. The proposed scheme is applied to a fault tolerant control design for flight control system.

• ETRI Journal
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• v.34 no.3
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• pp.450-453
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• 2012

IEEE 802.11n standards introduced a mixed-mode format frame structure to achieve higher throughput with multiple antennas while providing backward compatibility with legacy systems. Although multi-input multi-output channel estimation was possible only with high-throughput long training fields (HT-LTFs), the proposed scheme utilizes a legacy LTF as well as HT-LTFs in a decision feedback manner to improve the accuracy of the estimates. It was verified through theoretical analysis and simulations that the proposed scheme effectively enhances the mean square error performance.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.733-741
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• 2018

Capacity estimation is indispensable to ensure the safety and reliability of lithium-ion batteries in electric vehicles (EVs). Therefore it's quite necessary to develop an effective on-board capacity estimation technique. Based on experiment, it's found constant current charge time (CCCT) and the capacity have a strong linear correlation when the capacity is more than 80% of its rated value, during which the battery is considered healthy. Thus this paper employs CCCT as the health indicator for on-board capacity estimation by means of relevance vector machine (RVM). As the ambient temperature (AT) dramatically influences the capacity fading, it is added to RVM input to improve the estimation accuracy. The estimations are compared with that via back-propagation neural network (BPNN). The experiments demonstrate that CCCT with AT is highly qualified for on-board capacity estimation of lithium-ion batteries via RVM as the results are more precise and reliable than that calculated by BPNN.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.107-113
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• 2011

An OFDMA(Orthogonal Frequency Division Multiple Access) includes a MIMO(Multi-Input Multi-Output) scheme for improving spectral efficiency and data throughput. Recognizing that the performance of MIMO system is heavily dependent upon the accuracy of channel estimation, we propose a novel channel estimation for the MIMO scheme based on OFDMA. Conventional interpolation-based channel estimation suffers from poor estimation error at specific subcarriers. Proposed scheme makes use of a planar interpolation instead of linear interpolation for those subcarriers of bad accuracy. Simulation results show that the proposed scheme improves the performance of MIMO system by improving the accuracy in channel estimation especially for the adverse subcarrier positions. It is observed that the proposed scheme outperforms the conventional method by about 2dB in terms of both mean squared error and overall bit error rate with a reasonable computational complexity.