• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4099-4113
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• 2022

In this paper, we propose improved maximum access delay time, noise variance, and power delay profile (PDP) estimation schemes for orthogonal frequency division multiplexing (OFDM) system in multipath fading channels. To this end, we adopt the approximate maximum likelihood (ML) estimation strategy. For the first step, the log-likelihood function (LLF) of the received OFDM symbols is derived by utilizing only the cyclic redundancy induced by cyclic prefix (CP) without additional information. Then, the set of the initial path powers is sub-optimally obtained to maximize the derived LLF. In the second step, we can select a subset of the initial path power set, i.e. the maximum access delay time, so as to maximize the modified LLF. Through numerical simulations, the benefit of the proposed method is verified by comparison with the existing methods in terms of normalized mean square error, erroneous detection, and good detection probabilities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.65
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• pp.65-73
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• 2001

In this study, psychophysiological stress was quantitatively evaluated at various car interior noise levels by using Electroencephalogram(EEG). An experiment was performed to investigate the most comfortable range of noise level during simulated driving condition. Twelve healthy volunteers participated in the experiment. They were asked to operate the driving simulator while six levels of interior noise were given, such as 45dB(A), 50dB(A), 55dB(A), 60dB(A), 70dB(A), 80dB(A), and maximal subjective noise level. EEG signals were recorded for 60 seconds in each noise level. The power spectral analysis was performed to analyze EEG signal. At the same time, psychological stress was also measured subjectively by using a magnitude estimation method. The results showed that subjective stress and EEG spectrum indicated a statistically significant difference between noise levels. In particular, high level noise produced an increase in beta power at temporal(T3, T4) areas. It was also found that beta activity was highly correlated with subjective perception of discomfort, and subjects responded to car interior noise as arousing or negative stimuli. Moreover, beta power remained stable above 70dB(A), whereas subjective discomfort continued to increase even above 70dB(A) We concluded that brain waves could provide psychophysiological information of drivers emotional reaction to car interior noise. Thus, EEG parameters could be a new measure to determine optimal noise level in ergonomic workplace design after further verification in various experimental conditions.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.2
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• pp.173-178
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• 2010

Frequency is an important operating parameter of a power system. Due to the sudden change in generation and loads or faults in power system, the frequency is supposed to deviate from its nominal value. It is essential that the frequency of a power system be maintained very close to its nominal frequency. And monitoring and an accurate estimation of the power frequency by timing synchronized signal provided by FDR is essential to optimum operation and prevention for wide area blackout. As most conventional frequency estimation schemes are based on DFT filter, it has been pointed out that the gain error by change in magnitude could cause the defects when the power frequency is deviated from nominal value. In this paper, an advanced frequency estimation scheme using gain compensation for fault disturbance recorders (FDR) is presented. The proposed scheme can reduce the gain error caused when the power frequency is deviated from nominal value. Various simulation using both the data from EMTP package and user's defined arbitrary signals are performed to demonstrate the effectiveness of the proposed scheme. The simulation results show that the proposed scheme can provide better accuracy and higher robustness to harmonics and noise under both steady state tests and dynamic conditions.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.140-149
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• 2010

Green communication is a new paradigm of designing the communication system which considers not only the processing performance but also the energy efficiency. Power control management is one of the approaches in green communication to reduce the power consumption in distributed communication system. In this paper, we propose improved power control schemes for mobile satellite systems with ancillary terrestrial components (ATCs). In order to increase system capacity and reduce the transmitting power of the user's equipment, we propose an efficient channel estimation method consisting of a modified open-loop power control (OLPC) and closed-loop power control (CLPC). The OLPC works well if the forward and reverse links are perfectly correlated. The CLPC is sensitive to round-trip delay and, therefore, it is not effective in a mobile satellite system. In order to solve the above problem, we added monitoring equipment to both the OLPC and CLPC to use information about transmitting power that has not yet been received by the receiver over the satellite/ATC channel. Moreover, we adapted an efficient pilot diversity of both OLPC and CLPC in order to get a better signal to interference plus noise ratio estimation of the received signal.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.430-437
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• 2018

Ultrasonic attenuation is an important parameter in Quantitative Ultrasound and many algorithms have been proposed to improve estimation accuracy and repeatability for multiple independent estimates. In this work, we propose an improved algorithm for estimating ultrasonic attenuation utilizing the optimal frequency compounding technique based on stochastic noise model. We formulate mathematical compounding equations in the AWGN channel model and solve optimization problems to maximize the signal-to-noise ratio for multiple frequency components. Individual estimates are calculated by the reference phantom method which provides very stable results in uniformly attenuating regions. We also propose the guideline to select frequency ranges of reflected RF signals. Simulation results using numerical phantoms show that the proposed optimal frequency compounding method provides improved accuracy while minimizing estimation bias. The estimation variance is reduced by only 16% for the un-compounding case, whereas it is reduced by 68% for the uniformly compounding case. The frequency range corresponding to the half-power for reflected signals also provides robust and efficient estimation performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2050-2058
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• 2001

In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of 7he convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.66-73
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• 1996

In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise control(ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1506-1516
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• 1995

In this paper, we propose the filtered-x least mean fourth (FXLMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the FXLMF adaptive filter to active noise control requires to estimate the transfer characteristics of the acoustic path between the output and the error signal of the adaptive controller. The results of the convergence analysis of the FXLMF algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that the convergence behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06d
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• pp.80-83
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• 1998

In this paper, we propose a new filtered-x least mean fouth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior or a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the ouput and error signal of the adaptive canceller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct component . Phase estimation error and estimated again. In particular , the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.38-43
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• 1996

Windowing routines have as their purpose the reduction of the sidelobes of a spectral output of the FFT or DFT routines. Windowing routines accomplish this by forcing the beginning and end of any sequence to approach each other in value. Since they must work with any sequence they force the beginning and ending samples near zero. To make up for this reduction in power, windowing routines give extra weight to the values near the middle of the sequence. The difference between windows is the way in which they transition from the low weights near the edges to the higher weights neqr the middle of the sequence. Signal-to-noise ratio(SNR) can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing. Thus, the windowing operation improved the SNR of the noisy signal. This paper shows a performance estimation of windowing on a single tone with added Gaussian noise and uniform noise.