• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.2
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• pp.119-124
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• 1988

Real-time adaptive lattice predictor was implemented on the TMS32020 DSP chip for digital signal processing. The implemented system was composed of Input-Output units and centrla processing-control unit and its supporting assembly soft ware. The performance of hardware realization was verified by comparing input signal and one-step prediction signal which are calcualted by the real-time adaptive lattice predictor. As a result, for 4 stage lattice structure, the maximum running frequency was obtained as 6.41 KHz in this experiment.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.575-582
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• 2004

We explore the structure and usefulness of CERES plot as a basic tool for dealing with curvature as a function of the new predictor in generalized linear models. If a predictor has a nonlinear effect and there are nonlinear relationships among the predictors, the partial residual plot and augmented partial residual plot are not able to display the correct functional form of the predictor. Unlike these plots, the CERES plot can show the correct form. This is illustrated by simulated data.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.10a
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• pp.6-6
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• 1992

This work deals with nonlinear least squares method for estimating unknown universial constants C in a computer simulation code real experimental data(or database) and computer simulation data. The best linear unbiased predictor based on a spatial statistical model is fitted from the computer simulation data. Then nonlinear least squares estimation method is applied to the real data using the fitted prediction model(or simulation predictor) as if it were the true simulation model. An application to the computational nuclear fusion device is presented.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.141-145
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• 2009

In this paper, we propose an efficient lossless compression algorithm using spatial and temporal information. The proposed method obtains higher lossless compression of images than other lossless compression techniques. It is divided into two parts, a motion adaptation based predictor part and a residual error coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors. The predictor decides the proper selection of the spatial and temporal prediction values according to each past prediction error. The reduced error is coded by existing context coding method. Experimental results show that the proposed algorithm has better performance than those of existing context modeling methods.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1422-1426
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• 1987

In this paper, an adaptive DPCM scheme is presented for encoding monochrome images with easy hardware implementation at a transmission rate of exactly 1 bit/pel. The system is mainly composed of a compensated mean predictor and an adaptive two-level quantizer with backward estimation. In this system, the predictor is a sort of two-dimensional ARMA predictor in which a moving-average part is added to the conventional mean predictor. The quantizer adapts to the local statistics of its input without overhead information. To reduce annoying granular noise in the reconstructed image, Lee filter is used after reconstruction in the receiver.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1025-1030
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• 2009

It is known that the classical tuning formula for typical PID controllers in general provides unsatisfactory results for industrial plants where the time delay exceeds the dominant lag time. For this reason, alternative strategies have been studied in order to cope with this problem and the most popular scheme is the Smith Predictor(SP). In this paper, the dynamic model of a unit apartment in the district heating system, which is the control process effected by the dead-time, is developed, and the on/off room temperature control method with the SP simulate using Matlab-Simulink. The simulation results show that the SP works effectively in outdoor temperature variation.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.432-442
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• 2004

This paper presents a neural network predictor for analysing rigidity variations of hydrostatic bearing system. The designed neural network has feedforward structure with three layers. The layers are input layer, hidden layer and output layer. Two main parameter could be considered for hydrostatic bearing system. These parameters are the size of bearing pocket and the orifice dimension. Due to importancy of these parameters, it is necessary to analyse with a suitable optimisation method such as neural network. As depicted from the results, the proposed neural predictor exactly follows experimental desired results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.9-15
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• 2003

To improve the performance of PID controller of high order systems by model reduction, we proposed two model reduction methods. One, Original model with two point $({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$ in Nyquist curve used gradient base method and genetic algorithm. The other, Original model without two point$({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$in Nyquist curve used to add very small dead time. This method has annexed very small dead time on the base model for reduction, and we remove it after getting the reduced model, and , we improved Smith-predictor for a dead-time compensator using genetic algorithms. This method considered four points$({\angle}G(jw)=0,\;-\pi/2,\;-\pi,\;-3\pi/2)$ in the Nyquist curve to reduce steady state error between original and reduced model. It is shown that the proposed methods have more performance than the conventional method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.530-534
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• 1996

A novel phase error predictor is proposed for servo system in home-use VCRs. The multirate system in VCRs is converted into a single period sampling system with faster sampling time by using the proposed novel phase error predictor. And the disturbances can be measured much faster. From the experimental results, we can see that the perfomance of the control system is improved greatly. The phase lock time of the proposed servo system is ten times faster than that of the conventional system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1447-1453
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• 2008

In this paper, we proposed to improve performance of the design of a cascade controller with the smith-predictor structure. The parameters of controller in the inner loop are determined to minimize the integral of time multiplied by the absolute value of error (ITAE) value of performance Index. The controller of outer loop and parameters of Smith-Predictor can be obtain using reduction model. The model reduction is considered that it is the transient response and the steady-state response through the use of nyquist curve. Simulation examples are given to show the better performance of the proposed method than conventional methods.