• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1812-1824
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• 2016

The neural dynamics underlying the causal network during motor planning or imagery in the human brain are not well understood. The lack of signal processing tools suitable for the analysis of nonlinear and nonstationary electroencephalographic (EEG) hinders such analyses. In this study, noise-assisted multivariate empirical mode decomposition (NA-MEMD) is used to estimate the causal inference in the frequency domain, i.e., partial directed coherence (PDC). Natural and intrinsic oscillations corresponding to the motor imagery tasks can be extracted due to the data-driven approach of NA-MEMD, which does not employ predefined basis functions. Simulations based on synthetic data with a time delay between two signals demonstrated that NA-MEMD was the optimal method for estimating the delay between two signals. Furthermore, classification analysis of the motor imagery responses of 29 subjects revealed that NA-MEMD is a prerequisite process for estimating the causal network across multichannel EEG data during mental tasks.

• Journal of Aerospace System Engineering
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• v.14 no.4
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• pp.10-17
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• 2020

When an aircraft is taxiing, excitation force is applied according to the shape of the road surface. The sprung mass acceleration caused by the excitation of the road surface negatively affects the feeling of boarding. This paper addresses the verification process of the semi-active control method applied to improve the feeling of boarding. The Magneto-Rheological damper landing gear model is employed alongside the control method. It is a Oleo-Pneumatic damper filled with a fluid having the characteristics of increasing yield stress when subjected to a magnetic field. The control method involves verifying Skyhook Control Type2 developed by Skyhook control. The Sinozuka white noise model that considers runway characteristics was employed for the road surface in the simulation. The runway road surface obtained through this model has stochastic characteristics, so the dynamic characteristics were analyzed by applying Monte-Carlo simulation. A dynamic analysis was conducted by co-simulating the landing gear model made by RecurDyn and the control method designed by Simulink. Simulation results show that the Skyhook Control Type2 method has the best control effect in the low speed range compared to the passive type (without control) and skyhook control.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4C
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• pp.305-311
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• 2008

In this paper, we proposed an algorithm for adaptive noise cancellation (ANC) using the variable step size normalized least mean square (VSSNLMS) in real-time automobile environment. As a basic algorithm for ANC, the LMS algorithm has been used for its simplicity. However, the LMS algorithm has problems of both convergence speed and estimation accuracy in real-time environment. In order to solve these problems, the VSSLMS algorithm for ANC is considered in nonstationary environment. By computer simulation using real-time data acquisition system(USB 6009), VSSNLMS algorithm turns out to be more effective than the LMS algorithm in both convergence speed and estimation accuracy.

• Journal of Ocean Engineering and Technology
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• v.6 no.2
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• pp.41-45
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• 1992

In this paper an application technique of moment equation method to solution of nonlinear rolling equation of motion of ships is investigated. The exciting moment in the equation of rolling motion of ships is described as non-white noise. This non-white exciting moment is generated through use of a shaping filter. These coupled equations are used to generate moment equations. The nonstationary responses of the nonlinear system are obtained. The results are compared with those of a linear system.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.189-192
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• 1995

In Visually Evoked Potentials(VEP) or Auditory Evoked Potentials(AEP), the components by the stimulation and the components which are irrelevant to the stimulation(noise or nonstationary spontaneous EEG) are mixed together. So one should average hundreds of EP waves to extract the components by the stimulation only. In this study, we have classified EP's, which are the responses of the different stimulations and different states of subjects. To classify the EP waves, the cross-correlation coefficients and neural network method(error back propagation) are used and compared.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.697-707
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• 2017

In this paper, we propose a modified GARCH(p, q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p, q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1, 1)-X model studied by Han (2015) to various GARCH(p, q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1, 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p, q) model combined with proper additional covariate.

• 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㏈.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.159-168
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• 2002

A recently developed filbert-Huang transform (HHT) technique is applied to detect damage locations of bridge structures. The HHT may be used to identify the locations of damages which exhibit nonlinear and nonstationary behavior, since the HHT can show the instantaneous frequency characteristics of the signal. A series of numerical simulations were conducted for bridge pier systems with damages under a controlled load with sweeping frequency. The results of the numerical simulation study indicate that the HHT method can reasonably identify damage locations using a limited number of acceleration sensors under severe measurement noise condition.

• Journal of Astronomy and Space Sciences
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• v.23 no.3
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• pp.199-208
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• 2006

The terrestrial impact cratering record recently has been examined in the time domain by Chang & Moon (2005). It was found that the ${\sim}26$ Myr periodicity in the impact cratering rate exists over the last ${\sim}250$ Myrs. Such a periodicity can be found regardless of the lower limit of the diameter up to D ${\sim}35km$. It immediately called pros and cons. The aim of this paper is two-fold: (1) to test if reported periodicities can be obtained with an independent method, (2) to see, as attempted earlier, if the phase is modulated. To achieve these goals we employ the time/frequency analysis and for the first time apply this method to the terrestrial impact cratering records. We have confirmed that without exceptions noticeable peaks appear around ${\sim}25$ Myr, corresponding to a frequency of ${\sim}0.04(Myr)^{-1}$. We also find periodicities in the data base including small impact craters, which are longer. Though the time/frequency analysis allows us to observe directly phase variations, we cannot find any indications of such changes. Instead, modes display slow variations of power in time. The time/frequency analysis shows a nonstationary behavior of the modes. The power can grow from just above the noise level and then decrease back to its initial level in a time of order of 10 Myrs.

• Current Optics and Photonics
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• v.5 no.3
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• pp.322-328
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• 2021

In this paper, a pretreatment method for a matrix in convex optimization is proposed to optimize the spectral reconstruction process of a disordered dispersion spectrometer. Unlike the reconstruction process of traditional spectrometers using Fourier transforms, the reconstruction process of disordered dispersion spectrometers involves solving a large-scale matrix equation. However, since the matrices in the matrix equation are obtained through measurement, they contain uncertainties due to out of band signals, background noise, rounding errors, temperature variations and so on. It is difficult to solve such a matrix equation by using ordinary nonstationary iterative methods, owing to instability problems. Although the smoothing Tikhonov regularization approach has the ability to approximatively solve the matrix equation and reconstruct most simple spectral shapes, it still suffers the limitations of reconstructing complex and irregular spectral shapes that are commonly used to distinguish different elements of detected targets with mixed substances by characteristic spectral peaks. Therefore, we propose a special pretreatment method for a matrix in convex optimization, which has been proved to be useful for reducing the condition number of matrices in the equation. In comparison with the reconstructed spectra gotten by the previous ordinary iterative method, the spectra obtained by the pretreatment method show obvious accuracy.