• Proceedings of the KSR Conference
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• 2000.05a
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• pp.188-194
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• 2000

This study is about fault detection and fault area detection of LV circuit in Cab Cubicle system which have control of train to keep safety in High Speed Train. LV circuit is operated with diagnosis system like safety system. In this paper, we suggest a design and an implementation method to detect fault or to detect fault area automatically about LV circuit. The implemented system is tested successfully after implementation of some function. We expect reduction to diagnosis area or repair time by fault area module

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.5
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• pp.74-86
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• 2002

This paper proposes a VLSI architecture for high-speed data processing of the differential phase detectors with the decision feedback. To improve the BER performance of the conventional differential phase detection, DF-DPD, DPD-RGPR and DFDPD-SA have been proposed. These detection methods have the architecture feedbacking the detected phase to reduce the noise of the previous symbol as phase reference. However, the feedback of the detected phase results in lower data processing speed than that of the conventional differential phase detection. In this paper, the VLSI architecture was proposed for high-speed data processing of the differential phase detectors with decision feedback. The Proposed architecture has the pre-calculation method to previously calculate the results on 'N'th step at 'M-1'th step and the pre-decision feedback method to previously feedback the predicted phases at 'M-1'th step. The architecture proposed in this paper was implemented to RTL using VHDL. The simulation results show that the Proposed architecture obtains the high-speed data processing.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.12-20
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• 1993

In a conventional adaptive echo canceller, an ADF(Adaptive Digital Filter) with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to compute the coefficients, and NET detector using energy comparison method prevents the ADF to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yields more accurate detection of the start point of the NET signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.6
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• pp.299-306
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• 2000

The primary cause of air pollution by vehicles is imperfect combustion of fuel. One of the most usual causes of this imperfect combustion is the misfire in IC(Intenal Combustion) engine. Recently it is obligated for an ECU to monitor the emission level and warn the driver in case of exceeding specified emission standards. Therefore, in order to comply with this OBD-II regulations, car makers are investing a considerable amount into technology which would enable the detection of misfire and the particular cylinder in which misfire is taking place. So far, it has been able to detect misfire using engine speed, which can be obtained crank angle. However, such a method posed a problem in analyzing at high speed and in recognizing the misfire from the load impact at bumpy road. In this paper, misfire detection is made possible by simple arithmetic using WDFT, especially at high engine speed. In addition, the moving window method of a Walsh function is applied to determine the cylinders under misfire in case of multiple misfires. An actual experiment was conducted to prove that WDFT is applicable to effective in computation speed and to same result in misfire detection and cylinder determination at idle, part load and bumpy road conditions.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.955-957
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• 1998

Switched reluctance motor(SRM) has the advantages of simple structure, low rotor inertia, and high poer rate per unit volume. However, position sensor isessential in SRM in order to synchronize the phase excitation to the rotor position. The position sensors increase the cost of drive system, and tend to reduce system reliability. This paper investigtes the speed control of sensorless SRM. The proposed system consists of position detection circuit, dwell angle controller, digital logic commutator, PI speed controller and 4-phase inverter. The performances in the proposed system are verified through the experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.28-33
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• 2004

The measurement of wind speed gradient is very important for the detection of hazardous wind shear conditions since they are characterized by the abrupt shift of wind velocity and direction. These weather conditions usually imply high wind speed which requires a high PRF radar for the measurement. However, the measurement of a large absolute wind velocity is not necessary to obtain wind speed gradient. In this paper, a method was proposed to obtain wind speed gradient with a simple low PRF radar which may be very useful for the purpose of practical applications.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.109-117
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• 2023

Defect detection is one of the key factors in fabric quality control. To improve the speed and accuracy of denim fabric defect detection, this paper proposes a defect detection algorithm based on cascading feature extraction architecture. Firstly, this paper extracts these weight parameters of the pre-trained VGG16 model on the large dataset ImageNet and uses its portability to train the defect detection classifier and the defect recognition classifier respectively. Secondly, retraining and adjusting partial weight parameters of the convolution layer were retrained and adjusted from of these two training models on the high-definition fabric defect dataset. The last step is merging these two models to get the defect detection algorithm based on cascading architecture. Then there are two comparative experiments between this improved defect detection algorithm and other feature extraction methods, such as VGG16, ResNet-50, and Xception. The results of experiments show that the defect detection accuracy of this defect detection algorithm can reach 94.3% and the speed is also increased by 1-3 percentage points.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.677-680
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• 2003

Perceptual landmarks are an effective solution for a mobile robot realizing steady and reliable long distance navigation. But the prerequisite is those landmarks must be detected and recognized robustly at a higher speed under various lighting conditions. This made image processing more complicated so that its speed and reliability can not be both satisfied at the same time. Color based target detection technique can separate target color regions from non-target color regions in an image with a faster speed, and better results were obtained only under good lighting conditions. Moreover, in the case that there are other things with a target color, we have to consider other target features to tell apart the target from them. Such thing always happens when we detect a target with its single character. On the other hand, we can generally search for only one target for each time so that we can not make use of landmarks efficiently, especially when we want to make more landmarks work together. In this paper, by making use of the moment invariants of each landmark, we can not only search specified target from separated color region but also find multi-target at the same time if necessary. This made the finite landmarks carry on more functions. Because moment invariants were easily used with some low level image processing techniques, such as color based target detection and gradient runs based target detection etc, and moment invariants are more reliable features of each target, the ratio of target detection were improved. Some necessary experiments were carried on to verify its robustness and efficiency of this method.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.253-264
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• 2009

This paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of lane detection base on vision processing system. As a preprocessing for high speed lane detection, the vanishing line estimation and the optimal extraction of region of interest for lane boundary (ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled. Image feature information is extracted only in the ROI-LB. Road lane is extracted using a non-parametric model fitting and Hough transform within the ROI-LB. With simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since outliers of edge at each block can be removed with clustering of edge orientation for each block within the ROI-LB, the performance of lane detection can be greatly improved. The various real road experimental results are presented to evaluate the effectiveness of the proposed method.