• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.2
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• pp.126-136
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• 1997

When we apply the spectrally efficient quadrature amplitude modulation(QAM) to mobile communications, it is necessary to estimate and compensate the channel charac- teristics. In this paper, a new type fading estimation method for PSAM using sinc function is presented. Gaussian interpolation method has a drawback that the performance degrades rapidly if pilot symbol period increases even though pilot sysbol period is less than Nyquist sampling rate. The Wiener filter method does not degrade until pilot symbol period is equal to the Nyquist sampling rate. It is difficult for Wiener filter method to be applied to real system because autocorrelation function of channel gain, Doppler frequency and SNR(signal to noise ratio) must be known to optimize the filter coefficients. But proposed method has a similar performance to the Wiener filter method, and does not need to know the autocorrelation function of channel gain, the doppler frequency and SNR. Therefore the proposed method cna be applied to real system easily.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.512-527
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• 2013

This study examines the spatial distribution characteristics of financial industry which has been a necessary service for contemporary urban life. In particular, we analyze the spatial distribution patterns of money lending business which is considered with informal financial services as well as the spatial distribution patterns of banks which are representative of the institutional financial services. For the purpose, their density distribution patterns are explored by Kernel density analysis for both financial services in first. Moran's I coefficients are estimated for these two financial services to clarify the distintion in their geographical concentration patterns. The results of spatial autocorrelation analysis show stark differences between the center city and outskirts of the Seoul metropolitan area. Multivariate regression models are developed to explain the relationships between the spatial distributions of financial services and geographical variables. Finally, we discuss financial exclusion problem in the Metropolitan Seoul based on these spatial distribution characteristics.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.23-29
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• 2009

The heart sends blood to the body with heart rate. When heart rate for men is from 60 to 80 per minute, he is generally normal. However, if heart rate is less than the normal heart rate, the symptom is called by bradycardia. Otherwise, the symptom is called by tachycardia. These symptoms make him even to death. Therefore, heartbeat rate has a very important role in a healthy life. In this study, we studied on auto-extracting methods of heart rates from ECG, and compared them with those measured by naked eyes. The first auto-extracting method employs the 2-order differential equations to extract heart rate. The second method uses the autocorrelation coefficients to detect heart rate. To verify its efficacy and validity in practical applications, these method has been applied to MIT/BIH database.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.3-9
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• 2013

This paper proposes a selective-weighted energy detection (S-WED) and a synchronization algorithm appropriate for it in IR-UWB system. Energy detectors that are practical in terms of implementation are employed widely for noncoherent reception in IR-UWB systems. However, they show low performance due to using the energy samples captured at symbol rate. For this reason, weighted energy detectors are developed to improve the performance of EDs. Hence, for WED, not only synchronization but also the weight coefficients are needed to be obtained prior to data detection. Meanwhile, the optimal weighting coefficients of WEDs are known to be energy values. Therefore, synchronization and the weighting coefficients can be obtained simultaneously. This paper proposes an S-WED and a simple synchronization algorithm for it in which sub-intervals having energies under a certain level are excluded in energy accumulation resulting in a simpler WED with a bit performance increase in low SNR region. The proposed algorithm is verified through simulations using the preamble symbol and channel models defined in the IEEE 802.15.4a.

• Geophysics and Geophysical Exploration
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• v.19 no.4
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• pp.220-227
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• 2016

Marine seismic data have not only primary signals from subsurface but also ghost signals reflected from the sea surface. The ghost decreases temporal resolution of seismic data because it attenuates specific frequency components. For eliminating the ghost signals effectively, the exact ghost delaytimes and reflection coefficients are required. Because of undulation of the sea surface and vertical movements of airguns and streamers, the ghost delaytime varies spatially and randomly while acquiring seismic data. The reflection coefficient is a function of frequency, incidence angle of plane-wave and the sea state. In order to estimate the proper ghost delaytimes considering these characteristics, we compared the ghost delaytimes estimated with L-1 norm, L-2 norm and kurtosis of the deghosted trace and its autocorrelation on synthetic data. L-1 norm of autocorrelation showed a minimal error and the reflection coefficient was calculated using Kirchhoff approximation equation which can handle the effect of wave height. We applied the estimated ghost delaytimes and the calculated reflection coefficients to remove the source and receiver ghost effects. By removing ghost signals, we reconstructed the frequency components attenuated near the notch frequency and produced the migrated stack section with enhanced temporal resolution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.6
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• pp.815-823
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• 1993

In this paper, the structure of modified multiplication-free adaptive filter(M-MADF) and convergence analysis are presented. To evaluate the performance of proposed M-MADF algorithm, fractionally spaced equalizer (FSE) is used. The input signals are quantized using DPCM and the reference signals is processed using a first-order linear prediction filter, and the outputs are processed by a conventional adaptive filter. The filter coefficients are updated using the Sign algorithm. Under the assumption that the primary and reference signals are zero mean, wide-sense stationary and Gaussian, theoretical results for the coefficient misalignment vector and its autocorrelation matrix of the filter are driven. The convergence properties of Sign. MADF and M-MADF algorithm for updating of the coefficients of a digital filter of the fractionally spaced equalizer (FSE) are investigated and compared with one another. The convergence properties are characterized by the steady state error and the convergence speed. It is shown that the convergence speed of M-MADF is almost same as Sign algorithm and is faster that MADF in the condition of same steady error. Especially it is very useful for high correlated signals.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.9
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• pp.999-1004
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• 2014

In the present paper, the effects of initial crack location on spatial randomness of fatigue crack growth resistance (FCGR) in friction stir welded (FSWed) AA7075-T651 plates were studied. The objective of this study is to characterize the statistical properties of FCGR for three different types of initial crack location (ICL) specimens. In this work, the FCGR coefficients were treated as a spatial random process. It was found that the FCGR coefficients for all initial crack location specimens closely followed a two parameter Weibull distribution. The shape parameter of the Weibull distribution for BM-ICL specimens showed the largest value of 7.50, and that for the WM-ICL specimens showed the smallest value of 2.61. In addition, the autocorrelation functions for all the ICL specimens followed the exponential function.

• Journal of Biomedical Engineering Research
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• v.36 no.4
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• pp.103-108
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• 2015

Discrimination of Parkinson's disease (PD) from Essential tremor (ET) is often misdiagnosed in clinical practice. Since tremor is time-varying signal, and dominant and harmonic frequencies are shown in tremor only with moderate or severe symptom, there are some limitations to use frequency related features. Moreover, patients with PD or ET can suffer from both resting tremor and postural tremor. In this study, 28 patients with PD and 17 patients with ET were enrolled. Tremor was measured with accelerations on the more affected hand during resting and postural conditions. The ratio of root mean square (RMS) of resting tremor to RMS of postural tremor, the mean coefficients of autocorrelation function (ACF), and the mean of differences of two adjacent coefficients of ACF at resting and postural were calculated and compared between PD and ET. The performance showed 98% accuracy with support vector machine and leave-one-out cross validation. In addition, the method accurately differentiated the patients with tremor-dominant PD from patients with ET, with 100% accuracy. Therefore, the developed algorithm can assist clinicians in diagnosing and categorizing patients with tremor, especially, patients with mild symptom or the early stage of a disease, for proper treatment.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.17-24
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• 2014

This paper proposes a fault detection method for low-speed rolling element bearings of an induction motor using acoustic emission signals and histogram modeling. The proposed method performs envelop modeling of the histogram of normalized fault signals. It then extracts and selects significant features of each fault using partial autocorrelation coefficients and distance evaluation technique, respectively. Finally, using the extracted features as inputs, the support vector regression (SVR) classifies bearing's inner, outer, and roller faults. To obtain optimal classification performance, we evaluate the proposed method with varying an adjustable parameter of the Gaussian radial basis function of SVR from 0.01 to 1.0 and the number of features from 2 to 150. Experimental results show that the proposed fault identification method using 0.64-0.65 of the adjustable parameter and 75 features achieves 91% in classification performance and outperforms conventional fault diagnosis methods as well.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.507-516
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• 2012

We study time series models for seasonal time series data with a covariance structure that depends on time and the periodic autocorrelation at various lags $k$. In this paper, we introduce an ARMA model with periodically varying coefficients(PARMA) and analyze Arosa ozone data with a periodic correlation in the practical case study. Finally, we use a PARMA model and a seasonal ARIMA model for data analysis and show the performance of a PARMA model with a comparison to the SARIMA model.