• The KIPS Transactions:PartA
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• v.9A no.1
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• pp.75-82
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• 2002

A robust signal transition density propagation method for a zero delay model is presented to obtain the signal transition density for estimating the power consumption. The power estimation for the zero delay model is a proper criteria for the lower boundary of power consumption. Since the input characteristics are generally unknown at design stage, robust estimation for wide range input characteristics is very important for the power consumption. In this paper, a conventional transition estimation method will be explored. And this exploration will be analyzed with the input/output signal transition behavior and used to propose the robust signal transition density propagation for the power estimation. In order to apply to practical circuits, the reconvergent path, which is crucial to affect the exactness of the power estimation, will be studied and an algorithm to take the reconvergent path into consideration will be presented. In experiment, the proposed methodology shows better robustness, comparable accuracy and elapsed time compared to the conventional methods.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.4
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• pp.1-7
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• 2007

Flow rate is one of the important variables for precise motion control and detection of the faults and fluid loss in many hydraulic components and systems. But in many cases, it is not easy to measure it directly. The orifice area of a servo valve by which the fluid flows is one of key factors to monitor the flow rate. In this paper, we have constructed an estimation algorithm for the effective orifice area by using the model of a servo valve cylinder control system and Kalman filter algorithm. Without geometry information about the servo valve, it is shown that the effective orifice area can be estimated by using only displacement and pressure data corrupted with noise. And the effect of the biased sensor data and system parameter errors on the estimation results are discussed. The paper reveals that sensor calibration is important in accurate estimation and plausible parameter data such as oil bulk modulus and actuator volume are acceptable for the estimation without any error. The estimation algorithm can be used as an useful tool for detecting leakage, monitoring malfunction and/or degradation of the system performance.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.255-258
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• 2005

A blind-mode integer frequency offset estimation algorithm is proposed for an OFDM system. Imperfect integer frequency offset estimation causes ambiguity in the data sub-carrier position. Morelli's blind integer frequency offiet estimation algorithm exploits the likelihood function by comparing the power in sub-carriers. It, however, shows performance degradation when there is the fractional frequency offset. The proposed algorithm solves this by using interpolation in the frequency domain. In this algorithm, it is exploited that the effect of the frequency offset is shown as a shift of power spectrum. By calculating the covariance of over-sampled samples, most approximate samples to integer point are obtained. It enables integer frequency offset estimation less affected by fractional frequency offset.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.4
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• pp.39-47
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• 2020

We propose a multi-access points transmit power control algorithm in consideration of the channel estimation error and the multi-rate service. In the real communication systems, the channel estimation at the receiver side is imperfect due to limited number of pilot symbol usage. Furthermore, the multi-rate service is supported. We theoretically prove the uniqueness and the convergence of the proposed algorithm in multi-rate service environment. The proposed algorithm composes of one inner loop part and one outer loop part. Simulation results show that 1) the inner loop algorithm guarantees convergence of the transmit power level and the multi-rate service, 2) the outer loop algorithm compensates for the channel estimation error.

• 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.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.689-691
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• 2008

We present a novel power estimation technique for LCD panels. Our method considers the power consumed by each pixel as well as the inter-pixel power effect of the neighboring pixels. We implemented our method based on the table lookup model and its accuracy is about 98% compared to the actual measurements.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.101-108
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• 1988

In this paper the power spectrum of background EEG is estimated by the LMS PHD based on least mean square. At the power spectrum estimatiom, the stocastic process of background EEG is assumed to consist of the nonharmonic sinusoid and the white noise. In the LMS PHD the model parameters are obtained by the least mean square at optimal order which is obtained from the fact that the eigenvalue's fluctuation of autocorrelation matrix of the normal back-ground EEG is smaller at some order than at other order when the power spectrum of background EEG is esitmated by PHD. The optimal order of this model is the 6-th order when the eigenvalue's fluctuation of autocorrelation matrix of background EEG is considered. The estimation results are with compared the results from the Maximum Entropy Spectral Estimation and Pisarenko Harmonic Decomposition. From the comparison results. The LMS PHD is possible to estimate the power spectrum of background EEG.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.4
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• pp.566-574
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• 2013

In this paper, direct power control system for three-phase PFC AC/DC converter without the source voltage sensors is proposed. The sinusoidal input current and unity effective power factor are realised based on the estimated flux in the observer. Both active and reactive power calculated using estimated flux. The estimation of flux is performed based on the reduced-order virtual flux observer using the actual currents and the command control voltage. Moreover, source voltage sensors are replaced by a estimated flux. DC output voltage has been compensated by DC output ripple voltage estimation algorithm. The active and reactive powers estimation are performed based on the estimated flux and Phase angle. The proposed algorithm is verified through simulation and experiment.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.4
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• pp.294-297
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• 2021

A grid voltage estimation method for modular plug-in active power decoupling (APD) circuits is proposed in this study as direct replacements of electrolytic capacitors. Since modular plug-in APD circuits cannot have additional grid voltage sensors and should be operated independently without information exchange with the front-end converter, it is impossible to obtain the phase information of the grid directly. Therefore, the proposed method uses the second-order harmonic component of the DC-link voltage to estimate the grid voltage necessary to control the APD circuit. By employing the proposed method, the concept of modular plug-in APD circuits can be realized and implemented without direct detection of the grid voltage. The experimental results based on hardware-in-the-loop simulation (HILS) validate the effectiveness of the proposed control method.

• Nuclear Engineering and Technology
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• v.52 no.7
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• pp.1495-1502
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• 2020

A new method of X-ray source spectrum estimation based on compressed sensing is proposed in this paper. The algorithm K-SVD is applied for sparse representation. Nonnegative constraints are added by modifying the L₁ reconstruction algorithm proposed by Rosset and Zhu. The estimation method is demonstrated on simulated spectra typical of mammography and CT. X-ray spectra are simulated with the Monte Carlo code Geant4. The proposed method is successfully applied to highly ill conditioned and under determined estimation problems with a good performance of suppressing noises. Results with acceptable accuracies (MSE < 5%) can be obtained with 10% Gaussian white noises added to the simulated experimental data. The biggest difference between the proposed method and the existing methods is that multiple prior knowledge of X-ray spectra can be included in one dictionary, which is meaningful for obtaining the true X-ray spectrum from the measurements.