• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.425-434
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• 2020

Practical non-synoptic fluctuating wind often exhibits nonstationary features and should be modeled as nonstationary random processes. Generally, the coherence function of the fluctuating wind field has time-varying characteristics. Some studies have shown that there is a big difference between the fluctuating wind field of the coherent function model with and without time variability. Therefore, it is of significance to simulate nonstationary fluctuating wind field with time-varying coherent function. However, current studies on the numerical simulation of nonstationary fluctuating wind field with time-varying coherence are very limited, and the proposed approaches are usually based on the traditional spectral representation method with low simulation efficiency. Especially, for the simulation of multi-variable wind field of large span structures such as transmission tower-line, not only the simulation is inefficient but also the matrix decomposition may have singularity problem. In this paper, it is proposed to conduct the numerical simulation of nonstationary fluctuating wind field in one-spatial dimension with time-varying coherence based on the wavenumber-frequency spectrum. The simulated multivariable nonstationary wind field with time-varying coherence is transformed into one-dimensional nonstationary random waves in the simulated spatial domain, and the simulation by wavenumber frequency spectrum is derived. So, the proposed simulation method can avoid the complicated Cholesky decomposition. Then, the proper orthogonal decomposition is employed to decompose the time-space dependent evolutionary power spectral density and the Fourier transform of time-varying coherent function, simultaneously, so that the two-dimensional Fast Fourier transform can be applied to further improve the simulation efficiency. Finally, the proposed method is applied to simulate the longitudinal nonstationary fluctuating wind velocity field along the transmission line to illustrate its performances.

• Wind and Structures
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• v.39 no.2
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• pp.125-140
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• 2024

The simulation of non-stationary wind velocity is particularly crucial for the wind resistant design of slender structures. Recently, some data-driven simulation methods have received much attention due to their straightforwardness. However, as the number of simulation points increases, it will face efficiency issues. Under such a background, in this paper, a time-varying coherence matrix decomposition method based on Diagonal Proper Orthogonal Decomposition (DPOD) interpolation is proposed for the data-driven simulation of non-stationary wind velocity based on S-transform (ST). Its core idea is to use coherence matrix decomposition instead of the decomposition of the measured time-frequency power spectrum matrix based on ST. The decomposition result of the time-varying coherence matrix is relatively smooth, so DPOD interpolation can be introduced to accelerate its decomposition, and the DPOD interpolation technology is extended to the simulation based on measured wind velocity. The numerical experiment has shown that the reconstruction results of coherence matrix interpolation are consistent with the target values, and the interpolation calculation efficiency is higher than that of the coherence matrix time-frequency interpolation method and the coherence matrix POD interpolation method. Compared to existing data-driven simulation methods, it addresses the efficiency issue in simulations where the number of Cholesky decompositions increases with the increase of simulation points, significantly enhancing the efficiency of simulating multivariate non-stationary wind velocities. Meanwhile, the simulation data preserved the time-frequency characteristics of the measured wind velocity well.

• Wind and Structures
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• v.20 no.5
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• pp.661-682
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• 2015

This study investigates the use of time-frequency coherence analysis for detecting and evaluating coherent "structures" of surface pressures and wind turbulence components, simultaneously on the time-frequency plane. The continuous wavelet transform-based coherence is employed in this time-frequency examination since it enables multi-resolution analysis of non-stationary signals. The wavelet coherence quantity is used to identify highly coherent "events" and the "coherent structure" of both wind turbulence components and surface pressures on rectangular prisms, which are measured experimentally. The study also examines, by proposing a "modified" complex Morlet wavelet function, the influence of the time-frequency resolution and wavelet parameters (i.e., central frequency and bandwidth) on the wavelet coherence of the surface pressures. It is found that the time-frequency resolution may significantly affect the accuracy of the time-frequency coherence; the selection of the central frequency in the modified complex Morlet wavelet is the key parameter for the time-frequency resolution analysis. Furthermore, the concepts of time-averaged wavelet coherence and wavelet coherence ridge are used to better investigate the time-frequency coherence, the coherently dominant events and the time-varying coherence distribution. Experimental data derived from physical measurements of turbulent flow and surface pressures on rectangular prisms with slenderness ratios B/D=1:1 and B/D=5:1, are analyzed.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.841-848
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• 2008

This paper examined dynamic characteristics of high speed trains using a time varying frequency transform. Fourier transform based methods are frequently used for the calculation of the dynamic characteristics of trains in the frequency domain, but they cannot represent the time-varying characteristics. Therefore it is necessary to examine their characteristics using a time-varying frequency transform. For the examination, the non-stationary vibration of wheelset, bogie, and carbody are measured using accelerometers and stored in a data aquisition system. They are processed with localization of the data by modulating with a window function, and Fourier transform is taken to each localized data, called the short-time Fourier transform. From the processed results, time varying auto-spectral density, cross-spectral density, frequency response, and coherence functions have been calculated. From the analysis, it is confirmed that the time varying frequency transform is a useful method for analyzing the dynamic characteristics of high speed trains.

• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.527-534
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• 2013

In this study, we analyzed spatial-frequency relationship related brain function for change of the time during attentional visual stimulus through the analysis of Coherence. With experimentation about ERP(Event Related Potential)data, it revealed that change of the phase synchronization between different scalp locations at ${\theta}$, ${\alpha}$ band. ERP between left and right frontal lobes, between the frontal and central lobes showed the phase synchronization at the P100, N200, ERP between the frontal and occipital lobes showed the phase synchronization at the P300 related information of visual stimulus. Compared to STFT using the window of a fixed length, CWT is able to multi-resolution analysis with the adjustment of parameters of mother wavelet. Thus, coherence results with CWT was found to be effective for analysis of time-varying spatial-frequency relationship in ERP. The phase synchronization for inattentional visual stimulus was not observed.

• Wind and Structures
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• v.38 no.4
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• pp.277-293
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• 2024

The recorded thunderstorm winds at a point contain tri-directional components. The probabilistic characteristics of such recorded winds in terms of instantaneous mean wind speed and direction, and the probability distribution and the time-frequency dependent crossed and non-crossed power spectral density functions for the high-frequency fluctuating wind components are unclear. In the present study, we analyze the recorded tri-directional thunderstorm wind components by separating the recorded winds in terms of low-frequency time-varying mean wind speed and high-frequency fluctuating wind components in the alongwind direction and two orthogonal crosswind directions. We determine the time-varying mean wind speed and direction defined by azimuth and elevation angles, and analyze the spectra of high-frequency wind components in three orthogonal directions using continuous wavelet transforms. Additionally, we evaluate the coherence between each pair of fluctuating winds. Based on the analysis results, we develop empirical spectral models and lagged coherence models for the tri-directional fluctuating wind components, and we indicate that the fluctuating wind components can be treated as Gaussian. We show how they can be used to generate time histories of the tri-directional thunderstorm winds.

• ETRI Journal
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• v.38 no.4
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• pp.634-644
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• 2016

Channel-based radio-frequency fingerprinting such as a channel impulse response (CIR), channel transfer function (CTF), and frequency coherence function (FCF) have been recently proposed to improve the accuracy at the physical layer; however, their empirical performance, advantages, and limitations have not been well reported. This paper provides a comprehensive empirical performance evaluation of RF location fingerprinting, focusing on a comparison of received-signal strength, CIR-, CTF-, and FCF-based fingerprinting using the weighted k-nearest neighbor pattern recognition technique. Frequency domain channel measurements in the IEEE 802.11 band taken on a university campus were used to evaluate the accuracy of the fingerprinting types and their robustness to human-induced motion perturbations of the channel. The localization performance was analyzed, and the results are described using the spatial and temporal radio propagation characteristics. In particular, we introduce the coherence region to explain the spatial properties and investigate the impact of the Doppler spread in time-varying channels on the time coherence of RF fingerprint structures.

• The Journal of the Acoustical Society of Korea
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• v.35 no.3
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• pp.234-242
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• 2016

In this paper, an on-line noise coherence estimation algorithm for binaural speech enhancement system is proposed. A number of noise Power Spectral Density (PSD) estimation algorithms based on the noise coherence between two microphones have been proposed to improve the speech enhancement performance. In the conventional algorithms, the noise coherence was characterized using a real-valued analytic model. However, unlike the analytic model, the noise coherence between the two microphones is time-varying in real environments. Thus, in this paper, the noise coherence is updated in accordance with the variation of the acoustic environment to track the realistic noise coherence. The noise coherence can be updated only during the absence of speech, and the simulation results demonstrate the superiority of the proposed algorithm over the conventional algorithms based on the analytic model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1818-1826
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• 2014

Time-variant sea surface causes a forward scattering and Doppler spreading in received signal on underwater acoustic communication system. This results in time-varying amplitude, frequency and phase variation of the received signal. In such a way the channel coherence bandwidth and fading feature also change with time. Consequently, the system performance is degraded and high-speed coherent digital communication is disrupted. In this paper, quadrature phase shift keying (QPSK) performance is examined in two different sea surface conditions. The impact of sea surface scattering on performance is analyzed on basis of the channel impulse response and temporal coherence using linear frequency modulation (LFM) signal. The impulse response and the temporal coherence of the rough sea surface condition were more unstable and less than that of the calm sea surface condition, respectively. By relating these with time variant envelope, amplitude and phase of received signal, it was found that the bit error rate (BER) of QPSK are closely related to time variation of sea surface state.

• The Journal of the Acoustical Society of Korea
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• v.33 no.6
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• pp.413-419
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• 2014

Underwater acoustic channel has time-variability. Time varying channel which disturbs the continuous transmission of information data reduces the underwater acoustic communication performance. In this paper, we show the temporal coherence as time-variability of channel and indicate throughput efficiency in accordance with transmission time of information data. Then we analyzed influence of underwater channel time-variability on communication throughput efficiency. We confirmed that the throughput efficiency reduced when the time-variability of the channel increased via lake trial.