• 한국환경과학회지
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• 제23권6호
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• pp.1199-1211
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• 2014

The momentum flux and the sensible heat flux were measured with the scintillometers and ultrasonic anemometers at 6 sites of which surface characteristics like roughness length and zero-displacement are different each other. We estimated the momentum flux and the sensible heat flux based on the bulk transfer method with the drag coefficient and the heat transfer coefficient calculated from the temperature and wind speed at two heights. The variation of bulk transfer coefficients showed a remarkable difference depending on the atmospheric stability which is less influenced by the zero-displacement than the roughness length. The estimated sensible heat fluxes were in good agreement with those measured at 3 m, showing 23.7 $Wm^{-2}$ of the root mean square error that is less than 10% of its maximum. Since the estimated momentum flux is not only effected by drag coefficient but also by wind speed square, the determination of wind speed in the bulk transfer method is critical.

• 한국전기전자재료학회논문지
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• 제26권12호
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• pp.863-866
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• 2013

SiC crystal ingots were grown on 6H-SiC dual-seed crystals with different surface roughness and different seed orientation by a PVT (Physical Vapor Transport) method. 4H and 15R-SiC were grown on seed crystal with high root-mean-square (rms) value. The polytype of grown crystal on the seed crystal with lower rms value was confirmed to be 6H-SiC. On the other hand, all SiC crystals grown on seed crystals with different seed orientation were proven to be 6H-SiC. The surface roughness of seed crystals had no effect on the crystal structure of the grown crystals. However, the crystal quality of 6H-SiC single crystals grown on the on-axis seed were revealed to be slightly better than that of 6H-SiC crystal grown on the off-axis seed.

• Journal of information and communication convergence engineering
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• 제22권2호
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• pp.89-97
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• 2024

This research conducted a comparative analysis of two communication systems. The first system utilizes a conventional series configuration consisting of a symbol-rate least mean square (LMS) equalizer followed by a timing recovery loop. The second system introduces an innovative approach that integrates a symbol-rate LMS equalizer and a timing recovery component within a single loop, allowing mutual feedback between the two blocks. In this integrated system, the equalizer also provides timing error information, thereby eliminating the requirement for a separate threshold error detector. This study examines the performance curves of both system configurations. The simulation results revealed that the integrated system may offer improved stability in terms of multiple transmission challenges, including phase and frequency offsets and intersymbol interference. Further analysis and discussion highlight the significant insights and implications of the proposed architecture. Overall, the present findings provide an alternative perspective on the joint implementation of equalization and timing recovery in communication systems.

• 전기학회논문지P
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• 제64권4호
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• pp.267-272
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• 2015

Active noise control (ANC) is a method of cancelling a noise signal in an acoustic cavity by generating an appropriate anti-noise signal via canceling loudspeakers. The continuous progress of ANC involves the development of improved adaptive signal processing algorithms, transducers, and DSP hardware. In this paper, the convergence behavior and the stability of the FxLMS algorithm in ANC systems with real-time implementation is proposed. Specially, The advanced DSP H/W with dual core(DSP+ARM) and API(application programming interface) S/W programming was developed to improve the real-time implementation performance under the FxLMS algorithms of input noise such as road noise environment. The experimental results are found to be in good agreement with the theoretical predictions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.441-444
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• 1992

In this paper, for tracking and filtering seaway information which act as a control disturbance the adaptive notch filter which removes disturbance with fast convergence and stability without changing the value of gain parameter $\mu$ when statistical property of input signal varies rapidly is designed by improving conventional RMXMS(Recursive Maximum Mean Square) algorithm. Besides, in consideration of measurement noise of sensors in underwater vehicle, the system which removes the noise and the disturbance is suggested.

• Journal of applied mathematics & informatics
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• 제13권1_2호
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• pp.85-97
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• 2003

An indefinite stochastic linear-quadratic(LQ) optimal control problem with cross term over an infinite time horizon is studied, allowing the weighting matrices to be indefinite. A systematic approach to the problem based on semidefinite programming (SDP) and .elated duality analysis is developed. Several implication relations among the SDP complementary duality, the existence of the solution to the generalized Riccati equation and the optimality of LQ problem are discussed. Based on these relations, a numerical procedure that provides a thorough treatment of the LQ problem via primal-dual SDP is given: it identifies a stabilizing optimal feedback control or determines the problem has no optimal solution. An example is provided to illustrate the results obtained.

• 전자공학회논문지
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• 제50권9호
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• pp.172-176
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• 2013

This paper presents a modified filtered-x least mean square (FxLMS) algorithm to improve the stability of active noise control (ANC) system in realistic environment. A real-time ANC system employing modified FxLMS is designed and implemented on digital signal processor (DSP) board. The ANC system is evaluated for cancelling various tonal frequency noises in the range from 100 to 500 Hz and the performance is measured in terms of sound pressure level (SPL) attenuation. Experiment results show that a quiet zone with maximum 20 dB SPL attenuation can be generated around the location of error microphone.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 춘계학술대회 논문집
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• pp.119-123
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• 1996

The demands for robotic and automatic system are continually increasing in manufacturing fields. There were so many studies to monitor and predict system, but it were mainly relied upon measuring of cutting force, current of motor spindle and using acoustic sensor, etc. In this study digital image of time series sequence was acquired taking advantage of optical technique. Then, mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR model was selected for system model, fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, we found there was a system stability.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.681-684
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• 2000

Gradient-type algorithms for adaptive IIR notch filters are very attractive in terms of both performances and computational requirements. Generally, it is quite difficult to assess their performances analytically. There have been several trials to analyze such adaptive algorithms as the sign and the plain gradient algorithms for some types of adaptive IIR notch filters, but many of them still remain unexplored. Furthermore, analysis techniques used in those trials can not be directly applied to different types of adaptive IIR notch filters. This paper presents a detailed performance analysis of the sign algorithm for a well-known adaptive IIR notch filter with constrained poles and zeros, which can not be done by just applying the related existing analysis techniques, and therefore has not been attempted yet. The steady-state estimation error and mean square error (MSE) of the algorithm are derived in closed forms. Stability bounds of the algorithm are also assessed. extensive simulations are conducted to support the analytical findings.

• Journal of information and communication convergence engineering
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• 제19권4호
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• pp.241-247
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• 2021

Particulate matter has emerged as a serious global problem, necessitating highly reliable information on the matter. Therefore, various algorithms have been used in studies to predict particulate matter. In this study, we compared the prediction performance of neural network models that have been actively studied for particulate matter prediction. Among the neural network algorithms, a deep neural network (DNN), a recurrent neural network, and long short-term memory were used to design the optimal prediction model using a hyper-parameter search. In the comparative analysis of the prediction performance of each model, the DNN model showed a lower root mean square error (RMSE) than the other algorithms in the performance comparison using the RMSE and the level of accuracy as metrics for evaluation. The stability of the recurrent neural network was slightly lower than that of the other algorithms, although the accuracy was higher.