• ETRI Journal
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• v.31 no.3
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• pp.292-297
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• 2009

The power spectral density of a signal can be estimated most accurately by using a window with a narrow bandwidth and large sidelobe attenuation. Conventional windows generally control these characteristics by only one parameter, so there is a trade-off problem: if the bandwidth is reduced, the sidelobe attenuation is also reduced. To overcome this problem, we propose using a Butterworth window with two control parameters for power spectral density estimation and analyze its characteristics. Simulation results demonstrate that the sidelobe attenuation and the 3 dB bandwidth can be controlled independently. Thus, the trade-off problem between resolution and spectral leakage in the estimated power spectral density can be overcome.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.78-79
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• 1998

This paper describes a real time algorithm for blood flow estimation of LDF(laser Doppler flowmeter). Many algorithms for blood flow estimation are using power spectral density of Doppler signal by blood flow. In these research, the fast Fourier transformation is used to estimate power spectral density. This is a block processing procedure rather than real time processing. The algorithm in this paper used parametric spectral estimation. This has real time capability by estimation of AR(autoregressive) parameters sample by sample, and has smoothing power spectrum. Also, the frequency resolution is not limited by number of samples used to estimate AR parameter. Another advantage of this algorithm is that AR model enhance SNR.

• Structural Engineering and Mechanics
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• v.68 no.1
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.600-612
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• 2014

In this paper, we consider the problem of spectrum sensing for advanced television systems committee (ATSC) digital television (DTV) signal detection. To exploit the cyclostationarity of the ATSC DTV signals, we employ spectral correlation density (SCD) as the decision statistic and propose an optimal detection algorithm. The major difficulty is in obtaining the probability distribution functions of the SCD. To overcome the difficulty, we probabilistically model the pilot frequency location and employ Gaussian approximation for the SCD distribution. Then, we obtain a practically implementable detection algorithm that outperforms the industry leading systems by 2-3 dB. We also propose various techniques that greatly reduce the system complexity with performance degradation by only a few tenths of decibels. Finally, we show how robust the system is to the estimation errors of the noise power spectral density level and the probability distribution of the pilot frequency location.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.283-284
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• 2008

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.275-278
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• 1997

Standard methods estimating the power spectral density(PSD) from an irregularly sampled cardiac event series require deriving a new evenly-spaced signal applicable to those methods. To avoid that requirement, in this study, the power spectrum of heart rate variability was estimated by Lomb-Scargle's algorithm, which is a means of obtaining PSD estimates directly from irregularly sampled timeseries observed in astronomy. To assess the performance of Lomb-Scargle algorithm in the power spectral analysis of heart rate variability, it was applied to various cardiac event series derived through integral pulse frequency modulation model(IPFM) simulation and from real ECG signals, and the resultant power spectra was compared with those obtained by a conventional method based on the FFT. In result, it is concluded that Lomb-Scargle's periodogram is very effective in the power spectral analysis of heart rate variability, especially in the presence of arrhythmia and/or dropouts of cardiac events.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.108-113
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• 1997

In these days, customers require high-quality, high-performance, high-ride comfort for Automobile and then the automotive manufacturers concentrated on study of electrical, high-performance, low-cost of parts and sub-parts. In this paper, for ride comfort estimation PSD(Power Spectral Density) of acceleration at eight test point are measured, and then are calculated with new index of ride comfort. The new index of ride comfort developed for optimal design, real test, applied the actual. It can apply for various fields.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.319-325
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• 2020

In order to propose new satellite navigation signals, it is essential to analyze the increased level of interference effect that the existing signals suffer. In this paper, a method for estimating the power density of the interference signals on GPS signals is proposed before and after the additional transmission of the KPS signals in the L1, L2 and L5 bands. For estimation, we assume the number of visible satellites observed over the Korean peninsular and the minimum received power of the satellite navigation signals. The comparison of the estimated values shows that the power density of the interfering signal increases by up to 1.37 dB due to the introduction of KPS, but this leads to an increase in interference plus noise power density below 0.47 dB.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.271-282
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• 1996

this paper deal with the estimation of the power spectral density function of time series. A kernel estimator which is based on local average is defined and the rates of convergence of the pointwise, $$L_2$-norm; and; $L{\infty}$-norm associated with the estimator are investigated by restricting as to kernels with suitable assumptions. Under appropriate regularity conditions, it is shown that the optimal rate of convergence for 0$N^{-r}$ both in the pointwiseand $$L_2$-norm, while; $N^{r-1}(logN)^{-r}$is the optimal rate in the $L{\infty}-norm$. Some examples are given to illustrate the application of main results.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1342-1349
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• 2023

The planning accuracy of charged particle therapy (CPT) is subject to the accuracy of stopping power (SP) estimation. In this study, we propose a method of deriving a pseudo-triple-energy CT (pTECT) that can be achievable in the existing dual-energy CT (DECT) systems for better SP estimation. In order to remove the direct effect of errors in CT values, relative CT values according to three scanning voltage settings were used. CT values of each tissue substitute phantom were measured to show the non-linearity of the values thereby suggesting the absolute difference and ratio of CT values as parameters for SP estimation. Electron density, effective atomic number (EAN), mean excitation energy and SP were calculated based on these parameters. Two of conventional methods were implemented and compared to the proposed pTECT method in terms of residuals, absolute error and root-mean-square-error (RMSE). The proposed method outperformed the comparison methods in every evaluation metrics. Especially, the estimation error for EAN and mean excitation using pTECT were converging to zero. In this proof-of-concept study, we showed the feasibility of using three CT values for accurate SP estimation. Our suggested pTECT method indicates potential clinical utility of spectral CT imaging for CPT planning.