• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1875-1878
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• 2003

This paper Proposes a wavelet-based video compression method to improve compressed images using modification of wavelet coefficients. In conventional wavelet-based compression methods, bigger coefficients are transmitted early according to the significance of the coefficients. In this reason, when some coefficients which have more significance but are not bigger are not transmitted, image degradation occurs. The Proposed method considered two human visual characteristics. First, human eyes are more sensitive to the change of middle frequency which represents abrupt change of brightness than that of high frequency which expresses fine region. Second, human eyes are more dull to color component than luminance respectively. By adjusting the coefficients of wavelet transformed signals and allocating more bits for compression to the luminance signal, higher compression could be achieved.

• Journal of the Semiconductor & Display Technology
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• v.9 no.4
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• pp.57-61
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• 2010

The wavelet transform was adopted as the transform for JPEG2000. However, wavelet has weakness about smoothness along the contours and limited directional information. So we use to other transform, called contourlet transform in compression. Objective quality assessment methods currently used Peak signal to noise Ratio(PSNR). But that is not very well matched to perceived visual quality. So new image quality assessment is required. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. In addition we evaluated compression image quality using PSNR and SSIM. Finally contourlet transform has a good result about images with smooth contours and SSIM is good method for image evaluation compared to PSNR.

• Journal of Biomedical Engineering Research
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• v.12 no.3
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• pp.191-202
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• 1991

This paper describes ECG data compression algorithm using neural network. As a learning method, we use back error propagation algorithm. ECG data compression is performed using learning ability of neural network. CSE database, which is sampled 12bit digitized at 500samp1e/sec, is selected as a input signal. In order to reduce unit number of input layer, we modify sampling ratio 250samples/sec in QRS complex, 125samples/sec in P & T wave respectively. hs a input pattern of neural network, from 35 points backward to 45 points forward sample Points of R peak are used.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.101.1-101
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• 2002

Vehicle driving simulator is a virtual reality device which makes a human being feel as if the one drives a vehicle actually. Unlike actual vehicle, the simulator has limited kinematic workspace and bounded dynamic characteristics. So it is difficult to simulate dynamic motions of a multi-body vehicle model fully. In order to overcome these problems, washout algorithm which restricts workspace of the simulator within the kinematic limits is needed, and analysis of dynamic characteristics is required also. However, it is difficult to select the proper cutoff frequency of filters in washout algorithm. This paper introduces the signal compression method as an effective method to analyze the sim...

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.136-144
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• 1996

We developed a part of stroke sensing cylinder for position control of automatic excavator and its measurement system. In this paper, for development of stroke sensing cylinder, we consist of 2-axis control instrument system with Hall sensor. A performance of piston rod with magnetic scales is evaluated by the developed measurement system. Furthermore, the position control for good performance of instrument system is achieved by a sliding mode control which is a new method diminishing the chattering in that control by setting 2-dead band along the swtching line. The unknown parameters for sliding mode control are estimated by the signal compression method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.11
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• pp.2011-2020
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• 1992

This paper discusses about real time control applying sliding mode to robot manipulators whose nonlinear terms, which are inertia term, Corilis term and centrifugal force mterm, are regarded as disturbances. We could simplify the dynamic equations of a manipulator and servo system, which are composed of linear elements and nonlinear elements, by assuming that non-linear terms are external disturbance. By simplifying that equation, we could easily obtain a control input which satisfy sliding mode. We proposed a new control input algorithm to decrease chattering in the application of sliding mode control of manipulator whose nonlinear elements are regarded as disturbances. We could take impulse response of linear elements of dynamic equations of a robot manipulator and servo system by Signal Compression Method. So then, we could obtain the unknown parametes of its linear lements, which are used to obtain switching parameter satisfying sliding mode, by Signal Compression Method. In this experiments, we used DSP(Digital Signal Processor) controller to suppress chattering by obtaining a switching speed and to carry out real time control.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.541-547
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• 2013

Range resolution is important performance parameter to distinguish a target accurately. The destination of modern radar systems, to overcome the limitations of existing analog radar systems, is to improve the range resolution of the distance with low transmission power. For that reason, the research on pulse compression techniques is briskly studying. In the Receiver, modulation system of transmitted signal which has used in pulse compression technique is divided PM and FM to distinguish a target. In this paper, We analysed and designed the pulse compression signal processing module using the Baker Code which is the one of PM method's.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.253-256
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• 2000

In this paper, we propose the lossless image compression algorithm using the integer wavelet transform. Recently, the S＋P transform is widely used and computed with only integer addition and bit-shift operations, but not proper to remove the correlation of smooth images. then we compare the Harr wavelet of the S＋P transform with various integer coefficient filter banks and apply 9/7 ICFB to the wavelet transform. In addition, we propose a entropy-coding method that exploits the multiresolution structure and the feedback of the prediction error, and can efficiently compress the transformed image for progressive transmission. Simulation results are compared to the compression ratio using the S+P transform with different types of images.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.221-224
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• 1996

This paper presents the ECG data compression using wavelet transform(WT) and adaptive fractal interpolation(AFI). The WT has the subband coding scheme. The fractal compression method represents any range of ECG signal by fractal interpolation parameters. Specially, the AFI used the adaptive range sizes and got good performance for ECG data compression. In this algorithm, the AFI is applied into the low frequency part of WT. The MIT/BIH arrhythmia data was used for evaluation. The compression rate using WT and AFI algorithm is better than the compression rate using AFI. The WT and AFI algorithm yields compression ratio as high as 21.0 without any entroy coding.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.624-630
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• 2010

As electrocardiogram(ECG) signals are generally sampled with a frequency of over 200Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently. In this paper, an ECG signal compression method, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes are extracted with the proposed method, which uses local extremum of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes are added according to the iterative vertex selection method. Through the experimental results on the ECG signals from MIT-BIH Arrhythmia database, it is concluded that the vertexes selected by the proposed method preserve all feature points of the ECG signals. In addition, they are more efficient than the AZTEC(Amplitude Zone Time Epoch Coding) method.