• Journal of electromagnetic engineering and science
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• v.16 no.2
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• pp.80-86
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• 2016

This paper proposes the algorithm for forward link adaptive coding and modulation (ACM) and the detailed design for a satellite communication system to improve network reliability and system throughput. In the ACM scheme, the coding and modulation schemes are changed by as much as the channel can provide depending on the quality of the communication link. To implement the forward link ACM system in the Ka-band, channel prediction and modulation/coding decision methods are proposed and simulated. The parameters of the adaptive filter predictor based on the least mean square are optimized, the minimum mean square error of the channel predictor is 0.0608 when step size and the number of filter tap are 0.0001 and 4, respectively. A test-bed is set up to verify the forward link ACM system, and a test is performed using a Ka-band satellite (i.e., Communication, Ocean, and Meteorological Satellite [COMS]). This test verifies that the ACM scheme can increase the system throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2400-2413
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• 2019

Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1493-1496
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• 2011

Research results for LMS-based algorithms performances using real records of the traffic noise are discussed. The various algorithms based on LMS method are studied regarding their convergence speed and noise reduction index. Most effective algorithms are chosen for implementation in the active noise control barriers. The optimal step size, and number of adaptive filter taps are addressed during parametric study of the algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1373-1379
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• 2007

A modified adaptive switching median filter for impulse noise removal, which has the noise detection step and the noise filtering step, is proposed in this paper. In the noise detection step, we use the detection threshold which is earned by calculating the intensity differences between pixels nearby with each other in localized window, to determine whether the pixels in the image are noise or not. Then in the noise filtering step, we will only remove the corrupted pixels and remain the good pixels. By the noise detection result, we can easily get the local noise density of the image, and use it to consider the filtering mask size and the times of filtering iteration according to different localized noise corruptions. For Setting the simulation result, we compared the proposed method to conventional median filters with several test images corrupted by various impulse noise densities. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, the simulation results demonstrate that the proposed method shows better results than other median-based type filters.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.18-27
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• 2007

The conventional normalized least mean square (NLMS) algorithm is the most widely used for adaptive identification within a non-stationary input context. The convergence of the NLMS algorithm is independent of environmental changes. However, its steady state performance is impaired during input sequences with low dynamics. In this paper, we propose a new NLMS algorithm which is, in the steady state, insensitive to the time variations of the input dynamics. The square soot (SR)-NLMS algorithm is based on a normalization of the LMS adaptive filter input by the Euclidean norm of the tap-input. The tap-input power of the SR-NLMS adaptive filter is then equal to one even during sequences with low dynamics. Therefore, the amplification of the observation noise power by the tap-input power is cancelled in the misadjustment time evolution. The harmful effect of the low dynamics input sequences, on the steady state performance of the LMS adaptive filter are then reduced. In addition, the square root normalized input is more stationary than the base input. Therefore, the robustness of LMS adaptive filter with respect to the input non stationarity is enhanced. A performance analysis of the first- and the second-order statistic behavior of the proposed SR-NLMS adaptive filter is carried out. In particular, an analytical expression of the step size ensuring stability and mean convergence is derived. In addition, the results of an experimental study demonstrating the good performance of the SR-NLMS algorithm are given. A comparison of these results with those obtained from a standard NLMS algorithm, is performed. It is shown that, within a non-stationary input context, the SR-NLMS algorithm exhibits better performance than the NLMS algorithm.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.7
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• pp.569-581
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• 1989

This paper deals with a tracking algorithm based on integral projection which tracks moving targets with varying brightness and size. An adaptive windowing technique is employed to reduce the sensitivity of the system to the complex background image and also to reduce the computational load. The threshold value is determined by considering both the size and the threshold value of the brightness intensity of the recognized target obtained in the previous processing step. Window position is estimated by using the information of the velocity and acceleration of the target. And integral projection is applied to find the position of the target in the window accurately. Experimental results show that moving targets with varying brightness and size can be tracked properly in noisy environments.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.201-204
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• 2010

In the mobile healthcare system, a very important vital sign in analyzing the status of user health is the HRV (heart rate variability). The used signals for measuring the HRV are electrocardiograph and PPG (photoplethysmograph). In extracting the HRV from the PPG signal, an important issue is that extract the exactly HRV from PPG signal distorted from the user's movements. This study suggested a design method of the Kalman filter to solve the problem, and evaluated the performances of a proposed method by PPG signals containing motion artifacts. In the results of experiments that compared with a variable step size adaptive filter proposed in recently, the proposed method showed better performance than an adaptive filter.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.766-771
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• 1997

In this strip casting,size of the roll separating force is a index representing the solidifying status of the melt. Rolling forces at the start of the casting process can change abruptly due to the overcooling of the leader strip. This inconsistensy leads to machine damage or deficient solidification which results in the failure of the casting. In this study, a mathematical model is derived for the hydraulic servo pressure control system for the twin roll strip caster and its parameters are estimated by the RLS algorithm. Based on the identified model, an one-step ahead predictive control method is applied in order to minimize the transient fluctuation of the rolling force. Its simulation results are compared with those of the conventional PI controllers.

• Progress in Superconductivity and Cryogenics
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• v.16 no.4
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• pp.53-56
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• 2014

A numerical method of magnetic field calculation for the air-core solenoid is presented in this paper. In application of the Biot-Savart law, the magnetic field induced from the source current can be obtained by a double integration ormula. The numerical method named composite Simpson's rule for the integration is applied to the program and the adaptive quadrature method is used to adjust the step size in the calculation according to the precision we need. When the target point is in the solenoid and the intergrand's denominator may be zeroin the process of calculation, the method sill can provide an appropriate result. We have developed a program which calculates the magnetic field with at least 1ppm precision and named it as rzBI() to implement this method. The method has been used in the design of an MRI magnet, and the result show it is very flexible and convenient.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.183-184
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• 2007

As the mobile communication service is widely used, the demand for wireless repeaters is rapidly increasing because of the easiness of extending service areas. But wireless repeaters has a problem that the output of the transmit antenna is partially fed back to the receive antenna, which results in feedback interference. In this paper, we investigate the performance of adaptive variable step-size NLMS-based algorithms for cancelling the interference signals in the W-CDMA system under time-varying multipath channels. The criteria for comparison are tracking capability, convergence speed, and complexity.