• Journal of Korea Water Resources Association
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• v.43 no.5
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• pp.483-493
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• 2010

In this study, for the purpose of analyzing variability and periodicity of Korean hydrologic weather parameters, 5 hydrologic weather parameters data such as annual precipitation, annual rainy days, annual average temperature, annual average relative humidity, annual duration of sunshine are collected from 63 domestic meteorological stations that has the hydrologic weather parameters records more than 30 years. And in this study the variability and periodicity using the statistical methods like Wald-Wolfowitz test, Mann-Whitney test, and Wavelet Transform about hydrologic weather parameters is analyzed. The results of statistical analysis of variability and periodicity can be summarized as follows: 1) Variability commonly appeared in annual average temperature and annual average relative humidity. 2) Annual precipitation, annual rainy days and annual duration of sunshine showed different results according to area. 3) Periodicity appeared in annual precipitation and annual rainy days but did not appeard in annual average temperature, annual average relative humidity and annual duration of sunshine.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.441-448
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• 2007

Heart rate variability (HRV) in electrocardiogram (ECG) is an important index for understanding the health status of heart and the autonomic nervous system. Most HRV analysis approaches are based on the proper heart rate (HR) data. Estimation of heart rate is thus a key process in the HRV study. In this paper, we report an innovative method to estimate the heart rate. This method is mainly based on the concept of periodicity transform (PT) and instantaneous period (IP) estimate. The method presented is accordingly called the "PT-IP method." It does not require ECG R-wave detection and thus possesses robust noise-immune capability. While the noise contamination, ECG time-varying morphology, and subjects' physiological variations make the R-wave detection a difficult task, this method can help us effectively estimate HR for medical research and clinical diagnosis. The results of estimating HR from empirical ECG data verify the efficacy and reliability of the proposed method.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.53.1-53.1
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• 2021

Dwarf galaxies are the most abundant objects in the universe. Hence, understanding the dwarfs is important but relatively little is known due to the lack of computing power and limitations in the telescope resolution. We thus use the state-of-the-art NewHorizon simulation, which is a set of cosmological hydrodynamical simulations, to dissect the quenching mechanism working on dwarf galaxies by inspecting the star formation and mass history of individual galaxies. It is known that internal (AGN, SN, stellar feedback) and external (major and minor mergers, ram pressure stripping, strangulation) mechanisms affect the quenching of dwarfs. Because of the combination of these mechanisms, periodicity in the star formation history of the dwarf galaxies is expected. To check for their periodicity, Fourier transform was performed on the star formation history. By comparing the physical timescales and the periodicity, we determine the dominant effect working on the dwarfs. Then, we compare the dominant effects working on the galaxies according to their varying properties.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.831-837
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• 2006

The present study applies wavelet transform for the extraction of various periodicities which are included in TOC and pH time series of water quality and rainfall data. The primary objective of the present study is to detect the relationships between the respective data through the correlation analysis using the approximation components which are decomposed by wavelet transform. The results reveal the approximation components of TOC and pH in the 5th level of wavelet transform can explain more than 99% of the whole energy for the raw data respectively and there are considerably high correlation between the approximation components of the respective data used for the study even through no significant correlation between the raw data has been detected.

• The Journal of the Acoustical Society of Korea
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• v.37 no.5
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• pp.271-275
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• 2018

There are several methods for estimating the time delay between incoming signals to two sensors. Among them, the GCC-PHAT (Generalized Cross Correlation-Phase Transform) method, which estimates the relative delay from the signal whitening and the cross-correlation between the different signal inputs to the two sensors, is a traditionally well known method for achieving stable performance. In this paper, we have identified a part of GCC-PHAT that can improve the periodicity. Also, we apply the auto-correlation method that is widely used as a method to improve the periodicity. Comparing the proposed method with the GCC-PHAT method, we show that the proposed method improves the mean square error performance by 5 dB ~ 15 dB at the SNR above 0 dB for white Gaussian signal source and also show that the method improves the mean square error performance up to 15 dB at the SNR above 2 dB for the color signal source.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.365-373
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• 2019

In this study, we investigated the effect of wave height in coastal areas using discrete wavelet transform in Taehwa river basin in Ulsan. Through the decomposition result of tide data using daubechies level 7 wavelet and Curve Fitting Function, we confirmed that detail components of d₃ and d₄ were semidiurnal and diurnal components and approximation component(a₆) was the long period of lunar fortnight constituent. The decomposed tide data in six level was divided into tide component with periodicity and wave component with non-periodicity using autocorrelation function and fourier transform. Finally, we confirmed that the tide component is consisted 66% and wave component is consisted 34%. So, we quantitatively assessed the effect of wave on coastal areas. The result could be used for coastal flood risk management considering the effect of wave.

• Journal of Power Electronics
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• v.13 no.1
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• pp.170-176
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• 2013

Power converters produce a vast range of harmonics, subharmonics and interharmonics. Harmonics analyzing tools based on the Fast Fourier Transform (FFT) assume that only harmonics are present and the periodicity intervals are fixed, while these periodicity intervals are variable and long in the presence of interharmonics. Using FFT may lead to invalid and undesired results due to the above mentioned issues. They can also lead to problems such as frequency blending, spectral leakage and the picket-fence effect. In this paper, the group-harmonic weighting (GHW) approach has been presented to identify the interharmonics in a power system. Afterwards, a modified GHW has been introduced to calculate the proper bandwidth for analyzing the various values of interharmonics. Modifying this method leads to more precise results in the FFT of a waveform containing inter harmonics especially in power systems with a fundamental frequency drift or frequency interference. Numerical simulations have been performed to prove the efficiency of the presented algorithm in interharmonics detection and to increase the accuracy of the FFT and the GWH methods.

• Journal of Astronomy and Space Sciences
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• v.28 no.2
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• pp.103-108
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• 2011

The latitudinal variation of sunspots appearing during the period from 1874 to 2009 has been studied in terms of centerof-latitude (COL). The butterfly diagram has been used to study the evolution of the magnetic field and the dynamics at the bottom of the solar convection zone. Short-term periodicities have been of particular interest, in that they are somehow related to the structure and dynamics of the solar interior. We thus have focused our investigation on shortterm periodicities. We first calculated COL by averaging the latitude of sunspots with the weight function in area. Then, we analyzed the time series of COL using the wavelet transform technique. We found that a periodicity of ~5 years is the most dominant feature in the time series of COL, with the exception of the ~11 year solar cycle itself. This periodicity can be easily understood by considering small humps between the minima in the area-weighted butterfly diagram. However, we find that periodicities of ~1.3 (0.064), ~1.5 (0.056), or ~1.8 (0.046) years ($\frac{1}{month}$), month ), which have been previously suggested as evidence of links between the changing structure of the sunspot zone and the tachocline rotation rate oscillations, are insignificant and inconsistent. We therefore conclude that the only existing short-term periodicity is of ~5 years, and that periodicities of ~1.3, ~1.5, or ~1.8 years are likely to be artifacts due to random noise of small sunspots.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1321-1330
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• 2012

In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.197-200
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• 2000

This paper presents a time-based Pitch Determination Algorithm (PDA) for reliable estimation of pitch Period (PP) in speech signal. In proposed method, we use the Dyadic Wavelet Transform (DyWT), which detects the presence of Glottal Closure Instants (GCI) and uses the information to determine the pitch period. And, the proposed method also uses the periodicity property of DyWT to detect unsteady GCI. To evaluate the performance of the proposed methods, that of other PDAs based on DyWT are compared with what this paper proposed. The effectiveness of the proposed method is tested with real speech signals containing a transition between voiced and the unvoiced interval where the energy of voiced signal is unsteady. The result shows that the proposed method provides a good performance in estimating the both the unsteady GCI positions as well as the steady parts.