• ETRI Journal
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• v.43 no.6
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• pp.966-977
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• 2021

Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.29-32
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• 2015

It has been a big trend of the convergence technologies about communication systems and vehicular industry to improve safety and convenience. To achieve a number of infotainment vehicular applications, vehicles should transmit information with high reliability. A robust and accurate channel estimation scheme is of great importance to achieve the goal. In this paper, we present a novel enhanced decision-directed channel estimation scheme called FADP (Frequency Averaging Data Pilot) for dynamic time-varying vehicular channels in IEEE 802.11p. We use linear averaging filtering in frequency domain, and utilize the correlation characteristic of the channels between the adjacent two data symbols, update the CR in time domain to get more accuracy. Finally, analysis and simulation results reveal that compared with exist schemes, the proposed scheme has a good performance in mean square error (MSE) and bit error rate (BER).

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.11
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• pp.19-28
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• 2003

The limitation on the dynamic range improvement of the complementary correlation optical time domain reflectometer(CCOTDR) is presented. In CCOTDR, the improvement of dynamic range is function of both the averaging number of measurement cycles and the length of codes. The trade off between the averaging number and the code length restricts the improvement of the dynamic range and a very long code is not effective to improve the dynamic range. In this paper, the improvement limitation on dynamic range caused by the trade off between the averaging number and the code length is presented. For derivation of the trade off, the number of one measurement cycles employing a conventional single pulse method and employing a complementary code method are presented and compared. And the effective maximum code length is presented in addition.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1035-1042
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• 1988

The acoustic emission(AE) signal is monitored in milling operation in order to investigate the relationship between the progressive tool wear and the AE signals. A signal processing technique so called time domain averaging(TDA) is presented for the elimination of the influences of the noise imbedded in the periodic signals. The relationship between the progressive tool wear and the AE signals is investigated by varying the cutting speed, feed, depth of cut and the number of insert. From the measured data, it is observed that the averaged level of the AE signal increases at first with the increase of flank wear to a certain critical value, and then stays almost constant or fluctuates with further increase of the flank wear.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.84-89
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• 2014

Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.

• Korean Journal of Optics and Photonics
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• v.18 no.1
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• pp.44-49
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• 2007

We have transferred a narrow-linewidth $1.5{\mu}m$ laser beam through a 525 m fiber network with excellent transfer stability. The fiber-induced optical phase noise during the fiber transmission is cancelled by configuring a noise-canceling servo. The transfer instability was $2{\times}10^{-17}$ at 1 s of averaging time. We quantitatively analyzed the transferred optical frequency in the frequency domain and in the time domain.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.720-725
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• 1991

In this thesis, the lead-lag compensator is designed to improve output characteristics of flyback zero voltage switching quasi-resonant converters. The switch and the diode are assumed ideally. And the SMPS is modelled by state equations with four operation modes. And the model for controller design is also achived by using a state space averaging method, which is continuous time average of state variables every period. The lag, the lead and the lead-lag compensator is designed the SMPS respectively. The time domain analysis and the frequency domain analysis are done for each compensated circuit. It is possible increasing the phase margin and improving the transient response by the compensators. The phase lag compensator has small overshoot comparatively. But the bandwidth is narrower than the others, so it has longest settling time. For the phase lead compensator, the response come to steady-state within short period. But the overshoot is the largest due to its large peak gain. Finally, the phase lead-lag compensator has medium characteristics in the overshoot and the settling time.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.45-55
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• 1999

In this paper, we used the WLMS(Wavelet domain Least Mean Square) adaptive filter based on the wavelet transform to cancel grain noise. Usually, grain noise occurs in changes of the crystalline structure of metals in high temperature environment. It makes the detection of flaw difficult. The WLMS adaptive filtering algorithm establishes the faster convergence rate by orthogonalizaing the input vector of adaptive filter as compared with that of LMS adaptive filtering algorithm in time domain. We implemented the WLMS adaptive filter by using the delayed version of the primary input vector as the reference input vector and then implemented the CA-CFAR(Cell Averaging- Constant False Alarm Rate) threshold estimator. CA-CFAR threshold estimator enables to detect the flaw and back echo signals automatically. Here, we used the output signals of adaptive filter as its input signal. To Cow the statistical characteristic of ultrasonic signals corrupted by grain noise, we performed run test. The results showed that ultrasonic signals are nonstationary signal, that is, signals whose statistical properties vary with time. The performance of each filter is appreciated by the signal-to-noise ratio. After LMS adaptive filtering in time domain, SNR improves to about 2-3㏈ but after WLMS adaptive filtering in wavelet domain, SNR improves to about 4-6㏈.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.83-92
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• 2000

Sound intensity method is well known as a visualization technique of sound field or sound propagation in noise control. Sound intensity or energy flux is a vector quantity which describes the amount and the direction of net flow of acoustic energy at a given position. Especially two dimensional sound intensity method is very useful in evaluating periodic characteristics and acoustic propagation mode of noise source. In this paper, we have studied the noise source Identification, acoustic sound field analysis, and characteristics of noise source of rotary compressor and scroll compressor for air conditioner using complex sound intensity method. Also we proposed a now method of time domain analysis which is used in evaluating of position of noise source in rotary and scroll compressor in this paper This paper presents the advantage, simplicity and economical efficiency of this method by analysing the characteristics of noise source with two dimensional complex sound intensity simultaneously.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.1
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• pp.44-53
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• 1999

In this paper, we propose a pilot based time-averaging channel estimation method and analyze error performances for efficient transmission of OFDM(Orthogonal Frequency Division Multiplexing) in multipath fading environment. Frequency domain channel estimations have been used in OFDM systems to compensate signal distortions due to fading on each subcarrier. The frequency domain estimation scheme uses scattered pilot to estimate channel response by simple interpolation. This implies that the estimated channel response includes signal distortions due to the noise. In this paper, we propose time-averaged channel estimation method to remove the distortion by noise. The proposed scheme can effectively remove noise components by taking time-average of the estimated channel response after estimating frequency domain channel. The computer simulations were performed to evaluate the performance of the proposed channel estimator. For the Rician channel, we compared the performance of the proposed method to that of a conventional one using channel estimation by gaussian interpolation when SER(Symbol Error Rate) = $10^{-4}$, and compared to perfect channel estimation case. The proposed method showed differences of 0.07 dB, 0.6 dB compared to perfect channel estimation and improvements of 1.7 dB, 1.9 dB for 16 QAM, 64 QAM respectively compared to conventional method.