• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.225-229
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• 1998

If there is a mismatch between the controller programmed rotor time constant and the actual time constant of motor, the decoupling between the flux and torque is lost in an indirect rotor field oriented control. This paper presents a new estimation scheme for rotor time constant using artificial neural networks. The parameters of induction motor model organize 2 layer neural to be weight between neuron, which is proposed new in this paper. This method makes networks simple, so its brings not only the improvement in speed but simplification in calculation. Furthermore, it is possible to estimated rotor time constant real time through on-line learning without using off-line learning. The digital simulation and the experimental results to verify the effectiveness of the new method are described in this paper.

• 전기학회논문지P
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• 제58권4호
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• pp.385-390
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• 2009

This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

• 제어로봇시스템학회논문지
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• 제12권8호
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• pp.810-817
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• 2006

This paper presents a rotational motion estimation and correction technique for digital image stabilization. An equivalent rotation model is derived so as to accommodate a combined rotational and the translational motion. Thanks to this simplification, the suggested estimation algorithm can directly find the rotational center using geometric characteristic of local motion vectors instead of using searching method. And we also present recursive version of frame to reference algorithm(FRA) for the real time implementation. The proposed DIS system does not require time consuming parameter searching process, while showing comparatively good performance compared with the previous ones. To show the effectiveness of the DIS scheme, the algorithm has been implemented on the DSP based hardware system and experimental results are also discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권5호
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• pp.1369-1389
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• 2024

In the era of 6G, the rapid increase in communication data volume poses higher demands on traditional channel estimation techniques and those based on deep learning, especially when processing large-scale data as their computational load and real-time performance often fail to meet practical requirements. To overcome this bottleneck, this paper introduces quantum computing techniques, exploring for the first time the application of Quantum Generative Adversarial Networks (QGAN) to broadband channel estimation challenges. Although generative adversarial technology has been applied to channel estimation, obtaining instantaneous channel information remains a significant challenge. To address the issue of instantaneous channel estimation, this paper proposes an innovative QGAN with a dual-module design in the generator. The adversarial loss function and the Mean Squared Error (MSE) loss function are separately applied for the parameter updates of these two modules, facilitating the learning of statistical channel information and the generation of instantaneous channel details. Experimental results demonstrate the efficiency and accuracy of the proposed dual-module QGAN technique in channel estimation on the Pennylane quantum computing simulation platform. This research opens a new direction for physical layer techniques in wireless communication and offers expanded possibilities for the future development of wireless communication technologies.

• 한국농공학회:학술대회논문집
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• 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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• pp.512-518
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• 1999

Recently rainfall and water evel are monitored via on -line system in real-time bases. We applied the on-line system to get the rainfall and waterlevel data for the development of the real-time flood forecasting model based on SCS method in hourly bases. Main parameters for the model calibration are concentration time of flood and soil moisture condition in the watershed. Other parameters of the model are based on SCS TR-%% and DAWAST model. Simplex method is used for promoting the accuracy of parameter estimation. The basic concept of the model is minimizing the error range between forcasted flood inflow and actual flood inflow, and accurately forecasting the flood discharge some hours in advance depending on the concentration time. The flood forecasting model developed was applied to the Yedang and Topjung reservoir.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.330-335
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• 2002

Resistance spot welding is one of the most widely used processes in sheet metal fabrication. Quality assurance of welding has been important to increase the productivity. In this study, weld quality estimation using primary circuit dynamic resistance applied to the in-process real-time systems. For quality estimation, factors relating to quality were extracted from the dynamic resistance, measured in the timer. The relationship between these factors and weld quality was determined through a artificial neural network model. This method has the advantage over the conventional one, such as obtaining the quality information without the use of extra devices.

• 전기전자학회논문지
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• 제23권3호
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• pp.805-810
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• 2019

본 연구에서는 multitaper 기반의 스펙트럼 추정기법과 상태-공간 모델링 기반의 변수 추정 기법을 통합한 시간-주파수 분석 알고리즘을 제안한다. 일반적으로 시간-주파수 분석에는 불확실성 원리에 의해 시간 해상도와 주파수 해상도 사이에 트레이드오프 문제가 발생한다. 트레이드오프 문제를 최적화하기 위해서 short-time Fourier transform(STFT)와 wavelet 기반의 알고리즘들이 제안되었다. 본 논문의 저자는 다른 대안으로 상태-공간 프레임워크를 기반으로 한 새로운 multitaper 스펙트럼 추정 방법을 제안하였다. 그러나 기존의 방법은 스펙트럼이 시간에 따라 변하지 않는 경우에 잘 동작하지만, dynamic하게 변할 경우 제대로 추정하지 못하는 문제점이 있다. 그래서 본 논문에서는 상태-공간 모델에 사용되는 상태 노이즈와 관찰 노이즈를 주기적으로 업데이트 하는 방법을 제안하고자 한다. 우리는 제안 알고리즘을 시뮬레이션 데이터를 사용하여 테스트 하였고, 시간에 따라 변하는 스펙트럼에 대해서도 잘 동작하는 것을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권12호
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

• 한국생산제조학회지
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• 제5권2호
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• pp.63-72
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• 1996

In order to regulate the cutting force at a desired level during peripheral end milling processes a feedrate override Adaptive Control Constraint (ACC) system was developed. The feedrate override function was accomplished through a development of programmable machine controller (PMC) interface technique on the NC controller, Nonlinear model of the cutting process was linearized as an adaptive model with a time varying process parameter. An integral type estimator was introduced for on-line estimation of the cutting process parameter, Zero order hold digital control methodology which uses pole-assignment concept for tuning of PI controllers was applied for the ACC system. Performance of the ACC system wsa confirmed on the vertical machining center equipped with fanuc OMC through a large amount of experiment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 학술대회 논문집 전문대학교육위원
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• pp.162-166
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• 2000

In this paper, a maximum efficiency control technique of real-time processing in which parameter variation is compensated in vector control of an induction motors(I.M.) is proposed. Based on equivalent model of I.M., a loss minimization factor(LMF) with the variations of speed is derived. To solve problem of inaccuracy of LMF curves due to machine parameter variation, rotor resistance estimation is performed by using instantaneous reactive power. The estimated rotor resistance values are applied to the maximum efficiency control with a LMF.