• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.21-29
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• 1996

Industrial equipment, such as power plant, is required to operate reliably, continuously and economically under rather severe conditions of temperature, stress, and enbironment. To test structural integrity and fitness, ultrasonic nondestructive testing is used because of effectiveness and simplicity. In this paper, wavelet transform based least mean square(LMS) algorithm is applied to reduce the influence of the interference occurring between randomly positioned small scatters. The RUN test is performed to check the nonstationarity of the speckle noise signal. The performance of this new approach is compared with that of the time domain LMS algorithm by means of condition numbers, signal-to-noise ratio and 3-D image. As a result, the wavelet transform based LMS algorithm shows better performance than the time domain LMS algorithm in this experiment.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.445-466
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• 2004

In this paper, several modal identification techniques for output-only structural systems are extensively investigated. The methods considered are the power spectral method, the frequency domain decomposition method, the Ibrahim time domain method, the eigensystem realization algorithm, and the stochastic subspace identification method. Generally, the power spectral method is most widely used in practical area, however, the other methods may give better estimates particularly for the cases with closed modes and/or with large measurement noise. Example analyses were carried out on typical structural systems under three different loading cases, and the identification performances were examined throught the comparisons between the estimates by various methods.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.305-316
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• 1994

All physical data in the real world are nonstationary signals that have the time varying statistical characteristics. Although few algorithms suitable to process the nonstationary signals have ever been suggested, these are treated the nonstationary signals under the assumption that the nonstationary signal is a piece-wise stationary signal. Recently, statistical analysis algorithms for the nonstationary signal have concentrated so much interest. In this paper, nonstationary EMG signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be more smaller than that in the time domain. Then the model in the wavelet transform domain and an algorithm to estimate the model parameters are suggested. Also, an test signal generated by a white gaussian noise and the EMG signal are identified, and the algorithm performance is considered in the sense of the mean square error and the evaluation parameters.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.5 s.347
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• pp.34-47
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• 2006

In this paper, a new testing technique for core components of wireless transceiver was proposed. That was, band fault models (including the information of specifications in the analogue and RF IC) and methods which can test specifications in the time domain easily by observing a variation of band fault models in the circuit output were proposed and developed. This technique had an advantage over testing technique in frequency domain because it didn't need expensive test equipments and could reduce the time required. Test technique proposed in this paper was adapted to the test of 5.25 GHz low noise amplifier and proved that this testing technique was efficient in RF IC including low noise amplifier.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 1999.11a
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• pp.33-36
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• 1999

In this paper, we proposed a simultaneous switching noise(SSN) reduction technique in muti-layer beards(MLB) for high-speed digital applications and analyzed them using the Finite Difference Time Domain(FDTD) method. The new method by conductive dielectric substrates reduces SSN couplings and resonances, significantly, which cause series malfunctions in the modem high-speed digital applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.191-200
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• 2013

In this paper, we propose a new estimation method of time offset, frequency offset, and signal to interference plus noise ratio (SINR) using the synchronization channel preamble to provide IEEE 802.16.1a based talk-around direct communications (TDC). The proposed scheme estimates the time offset and frequency offset both in the time domain and in the frequency domain considering the preamble structure. In addition, it improves the estimation accuracy by combining the estimated values in two domains taking into account TDC synchronization scenarios. Through numerical simulations in the TDC channel environments, the performance of the proposed algorithm is compared with those of existing techniques such as the time domain estimation and the frequency domain estimation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.8-14
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• 2009

In the research field of speech recognition, pinpointing the endpoints of speech utterance even with the presence of background noise is of great importance. These noise present during recording introduce disturbances which complicates matters since what we just want is to get the stationary parameters corresponding to each speech section. One major cause of error in automatic recognition of isolated words is the inaccurate detection of the beginning and end boundaries of the test and reference templates, thus the necessity to find an effective method in removing the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two linear time-domain measurements: the short-time energy, and short-time zero-crossing rate. They perform well for clean speech but their precision is not guaranteed if there is noise present, since the high energy and zero-crossing rate of the noise is mistaken as a part of the speech uttered. This paper proposes a novel approach in finding an apparent threshold between noise and speech based on Lyapunov Exponents (LEs). This proposed method adopts the nonlinear features to analyze the chaos characteristics of the speech signal instead of depending on the unreliable factor-energy. The excellent performance of this approach compared with the conventional methods lies in the fact that it detects the endpoints as a nonlinearity of speech signal, which we believe is an important characteristic and has been neglected by the conventional methods. The proposed method extracts the features based only on the time-domain waveform of the speech signal illustrating its low complexity. Simulations done showed the effective performance of the Proposed method in a noisy environment with an average recognition rate of up 92.85% for unspecified person.

• Journal of the Optical Society of Korea
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• v.13 no.2
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• pp.272-278
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• 2009

Recently, there has been a growing interest in optical imaging of neural activity because the optical neuroimaging has considerable advantages over conventional imaging. Birefringence of the axon has been reported to change during neural activation, but the neurophysiological origin of the change is still unresolved. This study hypothesizes that the birefringence signal is at least partially attributed to the transient cellular volume change associated with nerve excitation. To examine this hypothesis, we investigated how the intensity of cross-polarized light transmitting through the axon would change as the size of the axon changes. For this purpose, a two-dimensional finite-difference time-domain program was developed with the improvement of the total-field/scattered-field method which reduces numerical noise. The results support our hypothesis in that the computed cross-polarized signals exhibit some agreement with previously-reported birefringence signals.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.4
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• pp.62-68
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• 2001

In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electrical detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, included noise signal in detected PD signal is well eliminated. we can propose the true shine of PD signal.

• Structural Engineering and Mechanics
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• v.29 no.3
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• pp.241-258
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• 2008

This paper presents a new identification approach to prestress force. Firstly, a bridge deck is modeled as a prestressed Timoshenko beam. The time domain responses of the beam under sinusoidal excitation are studied based on modal superposition. The prestress force is then identified in the time domain by a system identification approach incorporating with the regularization of the solution. The orthogonal polynomial function is used to improve the noise effect and obtain the derivatives of modal responses of the bridge. Good identification results are obtained from only the first few measured modal data under both sinusoidal and impulsive excitations. It is shown that the proposed method is insensitive to the magnitude of force to be identified and can be successfully applied to indirectly identify the prestress force as well as other physical parameters, such as the flexural rigidity and shearing rigidity of a beam even under noisy environment.