• Journal of the Korean Statistical Society
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• v.20 no.1
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• pp.29-43
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• 1991

Two data-based bandwidth selectors which are optimal in the sense that they achieve n$\^$-$\frac{1}{2}$/ rate of convergence in kernel density estimation are proposed. The proposed bandwidth selectors are constructed by modifying Park and Marron's plug-in method. The first modification is taking Taylor expansion of the mean integrated squared error to two more terms than in the case of plug-in method. The second is estimating more accurately the functionals of the unknown density appeared in the minimizer of the expansion by using higher order kernels. The proposed bandwidth selectors were proved to be optimal in terms of convergence rate. According to small-sample Monte Carlo studies, the proposed bandwidth selectors showed better performance than all the other bandwidth selectors considered in the simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.565-569
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• 2003

In this paper, a robust filter is proposed to effectively estimate the system states in the case where system model uncertainties as well as disturbances are present. The proposed robust filter is constructed based on the linear approximation methods for a general nonlinear uncertain system with an integral quadratic constraint. We also derive the important characteristic of the proposed filter, a modified $H_{\infty}$ performance index. Analysis results show that the proposed filter has robustness against disturbances, such as process and measurement noises, and against parameter uncertainties. Simulation results show that the proposed filter effectively improves the performance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.408-413
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• 2005

A new methodology for discrete non-Gaussian probability density estimation is investigated in this paper based on a dynamic Bayesian network (DBN) and kernel functions. The estimator consists of a DBN in which the transition distribution is represented with kernel functions. The estimator parameters are determined through a recursive learning algorithm according to the maximum likelihood (ML) scheme. A discrete-type Poisson distribution is generated in a simulation experiment to evaluate the proposed method. In addition, an unknown probability density generated by nonlinear transformation of a Poisson random variable is simulated. Computer simulations numerically demonstrate that the method successfully estimates the unknown probability distribution function (PDF).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.941-948
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• 2006

In this study, the new method for reliability estimation is proposed using kriging metamodel. Kriging metamodel can be determined by appropriate sampling range and sampling numbers because there are no random errors in the Design and Analysis of Computer Experiments(DACE) model. The first kriging metamodel is made based on widely ranged sampling points. The Advanced First Order Reliability Method(AFORM) is applied to the first kriging metamodel to estimate the reliability approximately. Then, the second kriging metamodel is constructed using additional sampling points with updated sampling range. The Monte-Carlo Simulation(MCS) is applied to the second kriging metamodel to evaluate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.294-301
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• 2016

In this paper, we present methods to efficiently parallelize iterative 3D image reconstruction by exploiting trigeneous devices (three different types of device) at the same time: a CPU, an integrated GPU, and a discrete GPU. We first present a technique that exploits single instruction multiple data (SIMD) architectures in GPUs. Then, we propose a performance estimation model, based on which we can easily find the optimal data partitioning on trigeneous devices. We found that the performance significantly varies by up to 6.23 times, depending on how SIMD units in GPUs are accessed. Then, by using trigeneous devices and the proposed estimation models, we achieve optimal partitioning and throughput, which corresponds to a 9.4% further improvement, compared to discrete GPU-only execution.

• Journal of Power Electronics
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• v.11 no.4
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• pp.599-605
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• 2011

This paper proposes a gain scheduling method that improves the stability of grid-connected systems employing an LCL-filter. The method adjusts the current controller gain through an estimation of the grid impedance in order to reduce the resonance that occurs when using an LCL-filter to reduce switching harmonics. An LCL-filter typically has a frequency spectrum with a resonance peak. A change of the grid-impedance results in a change to the resonant frequency. Therefore an LCL-filter needs a damping method that is applicable when changing the grid impedance for stable system control. The proposed method instantaneously estimates the grid impedance and observes the resonant frequency at the same time. Consequently, the proposed method adjusts the current controller gain using a gain scheduling method in order to guarantee current controller stability when a change in the resonant frequency occurs. The effectiveness of the proposed method has been verified by simulations and experimental results.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.126-131
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• 2015

When a battery is discharging, the battery's current and terminal voltage must both be measured to estimate its state of charge (SOC). If the SOC can be estimated by using only the current or voltage, hardware costs will decrease. This paper proposes an SOC estimation algorithm that needs to measure only the terminal voltage while a battery is discharging. The battery's SOC can be deduced from its open circuit voltage (OCV) through the relationship between SOC and OCV. But when the battery is discharging, it is not possible to measure the OCV due to the voltage drop in the battery's internal resistance (IRdrop). The proposed algorithm calculates OCV by estimating IRdrop using a dynamic terminal voltage measurement. This paper confirms the results of applying the algorithm in a hardware environment via algorithm binarization. To evaluate the algorithm, a Simulink battery model based on actual values was used.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.935-940
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• 2002

For robot navigation and visual reconstruction, structure from motion (SFM) is an active issue in computer vision community and its properties arc also becoming well understood. In this paper, when using stereo image sequence and direct method as a tool for SFM, we present a new method for overcoming bas-relief ambiguity. We first show that the direct methods, based on optical flow constraint equation, are also intrinsically exposed to such ambiguity although they introduce robust methods. Therefore, regarding the motion and depth estimation by the robust and direct method as approximated ones. we suggest a method that refines both stereo displacement and motion displacement with sub-pixel accuracy, which is the central process f3r improving its ambiguity. Experiments with real image sequences have been executed and we show that the proposed algorithm has improved the estimation accuracy.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.254-264
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• 2007

A promising approach to improve the performance of mobile location system is the use of antenna arrays in both transmitter and receiver sides. Using advanced array signal processing techniques, such multiple-input multiple-output (MIMO) communication systems can offer more mobile location information by exploiting the spatial properties of the multipath channel. In this paper, we propose a novel approach to determine the position of mobile terminal based on estimated multipath signal parameters using only one base station in MIMO communication systems. This approach intends to minimize the error occurring from the estimation of multiple paths and gives an optimal estimation of the position of mobile terminal by simultaneously calculating a set of nonlinear location equations. This solution breaks the bottleneck of conventional mobile location systems which have to require multilateration of at least three base stations.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.957-966
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• 1999

We evaluate the accuacy and precision of maximum likelihood estimation procedures for infectivity of HIV in partner studies. This is achieved by applying the oricedyre typothetical samples generated by computer. One hundred samples were generated with various combinations of parameters. The estimation procedure was found to be quite accurate. in addition it was found that the power of the test for equality of infectivities for two types of contact depends on sample size and length of observation period but not on the number of observations made on each subject. Tests based on a model for the infectivity had higher power than standard methods for comparing proportions.