• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.145-145
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• 2000

In this paper, we propose a hybrid d-step predictor which is composed of an adaptive predictor and a Kalman predictor. We prove the performance limit of the proposed predictor. Simulation is conducted to examine the performance of the proposed predictor. Simulation results show that the proposed combined predictor is superior to the adaptive predictor and the Kalman predictor. Proposed predictor is used for prediction of gun tip vibration of k1 tank. The result is compared with that of conventional adaptive predictor.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art 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.

• Journal of IKEEE
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• v.13 no.1
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• pp.36-40
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• 2009

In control of time delay systems, if the informations about the system model and the disturbance can be estimated exactly, the ideal response can be achieved by using Smith predictor controller. Therefore, in this paper, an adaptive algorithm is proposed to control time delay systems existing modelling errors and disturbance. An adaptive observer to estimate disturbance and system model is designed and adaptive laws adjusting the observer are proposed. The new Smith predictor controller is designed using the proposed adaptive observer. As a result, the proposed controller can eliminate the effects of the disturbance and the modelling error. The effectiveness and the improved performance of the proposed system are verified by computer simulation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.435-441
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• 2017

Detecting an inter-harmonic accurately is not easy work, because it has small magnitude, and its frequency which can be observed is not an integer multiple of fundamental frequency. In this paper, a new method using filter bank system and adaptive predictor is proposed. Filter bank system decomposes input signal to sub bands. In adaptive predictor, inter-harmonic is detected with decomposed sub band signal as input, and error signal as output. In this scheme, input-output characteristic of adaptive predictor is notch filter, as predicted harmonic is canceled in error signal, so detecting an inter-harmonic can be possible. Magnitude and frequency of detected inter-harmonic is estimated by recursive algorithm. The performances of proposed method are evaluated to sinusoidal signal model synthesized with harmonics and inter-harmonics. And validity of the method is proved as comparing the inter-harmonic detection results to MUSIC and ESPRIT.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.209-213
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• 2010

In this paper, an efficient predictor for entropy coding is proposed. It adaptively selects one of two prediction errors obtained by MED(median edge detector) or GAP(gradient adaptive prediction). The reduced error is encoded by existing entropy coding method. Experimental results show that the proposed algorithm can compress higher than existing predictive methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1676-1679
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• 2007

In control of the time delay systems, if the disturbance information can be estimated exactly, the ideal response for the disturbance can be achieved. Therefore, in this paper, a new adaptive disturbance observer for the time delay system control is proposed. The disturbance observer is designed and adaptive laws for adjusting the observer are proposed. The new Smith predictor controller to eliminate the effects of the disturbance can be achieved by adding an estimated disturbance to the Smith model. The improved performances of the proposed system and the adaptive disturbance observer are verified by computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.2
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• pp.210-217
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• 1990

For the failure detection of dynamic systems, processing the residuals from the observer of the estimator is the most general method. A failure detection method which use an adaptive predictor to separate the effect of sensor failure from the additive noise in the residuals of a Kalman filter that is employed as an estimator of a dynamic system is addressed here. In the method, the property of the residuals of an optimal Kalman estimator is exploited. The simulation results of this method shows that the proposed method is superior to the sequential probability ratio test for a small failure magnitude.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.143-144
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• 2006

This paper presents an adaptive OFDM system with multistep predictor to effectively compensate multiple feedback delays. The proposed scheme adaptively changes the modulation order per subcarrier based on the predicted CSI to improve data capacity and system performance.