• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.449-451
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• 2003

The estimation of time-series data is fundamental process in many data analysis cases. However, the unwanted measurement error is usually added to true data, so that the exact estimation depends on efficient method to eliminate the error components. The wavelet transform method nowadays is expected to improve the accuracy of estimation, because it is able to decompose and analyze the data in various resolutions. Therefore, the wavelet based Kalman filter method for the estimation of time-series data is proposed in this paper. The wavelet transform separates the data in accordance with frequency bandwidth, and the detail wavelet coefficient reflects the stochastic process of error components. This property makes it possible to obtain the covariance of measurement error. We attempt the estimation of true data through recursive Kalman filtering algorithm with the obtained covariance value. The procedure is verified with the fundamental example of Brownian walk process.

• Journal of Elementary Mathematics Education in Korea
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• v.19 no.3
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• pp.267-287
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• 2015

In this paper, based on the results of analysis on types and strategies of estimation in measurement in the textbooks according to 2009 revised elementary mathematics curriculum, the following four implications are suggested for curriculum development and textbook development for a later date. First, it is necessary to reconcile curriculum and textbooks in contents for estimation in measurement. In 2009 revised elementary mathematics curriculum, only estimation in length, estimation in capacity, estimation in weight, estimation in angular measure are presented. However, estimation in time and estimation in area are presented in textbooks. Second, it is necessary to introduce various strategies for estimation in measurement. In teacher's manual, three strategies like using referent, chunking, unitizing are illustrated. But in textbooks, such strategies are not illustrated properly. Third, the meaning of the 'estimate' need to be clarified. In textbooks, 'estimate' are used also in other contexts. Fourth, it is necessary to clarify whether or not to deal with estimation in time, estimation in area, and estimation in volume in the school curriculum. In 2009 revised elementary mathematics curriculum, estimation in time, estimation in area, and estimation in volume are not mentioned explicitly.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.55-76
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• 2000

We propose a general solution methodology for identifying the optimal aggregation interval sizes as a function of the traffic dynamics and frequency of observations for four cases : i) link travel time estimation, ii) corridor/route travel time estimation, iii) link travel time forecasting. and iv) corridor/route travel time forecasting. We first develop statistical models which define Mean Square Error (MSE) for four different cases and interpret the models from a traffic flow perspective. The emphasis is on i) the tradeoff between the Precision and bias, 2) the difference between estimation and forecasting, and 3) the implication of the correlation between links on the corridor/route travel time estimation and forecasting, We then demonstrate the Proposed models to the real-world travel time data from Houston, Texas which were collected as Part of the Automatic Vehicle Identification (AVI) system of the Houston Transtar system. The best aggregation interval sizes for the link travel time estimation and forecasting were different and the function of the traffic dynamics. For the best aggregation interval sizes for the corridor/route travel time estimation and forecasting, the covariance between links had an important effect.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.792-799
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• 2008

Motion estimation is crucial in a remote control for its convenience or accuracy. Time delays, however, can occur in the problem because data communication is required through a network. In this paper, state estimation problem with uncertain time delayed measurements is addressed. In dynamic system with noise, after taking measurements, it often requires some time until that is available in the filter algorithm. Standard filters not considering this time delays cannot be used since the current measurement is related with a past state. These delayed measurements are solved with augmented extended Kalman filter, and the uncertainty of delayed time is also resolved based on an explicit formulation. The proposed method is analyzed and verified by simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1013-1020
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• 2013

In this paper the super-resolution time delay estimation algorithms based on eigen-analysis are developed for spread spectrum signals along with their comparative performance analysis. First, we shall develop super-resolution time delay estimation algorithms using the representative eigen-analysis based AOA (angle-of-arrival) estimation algorithms such as MUSIC, Minimum-Norm, and ESPRIT, and apply them to the ISO/IEC 24730-2.1 real-time locating system (RTLS) employing a direct sequence spread spectrum (DS-SS) technique to compare their performances in RTLS environments. Simulation results illustrate that all the three algorithms can resolve multipath signals whose delay differences are even smaller than the Rayleigh resolution limit. Simulation results also show that MUSIC and Minimum-Norm provide a similar performance while ESPRIT is inferior to both algorithms in RTLS environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.722-727
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• 2010

This paper presents Dynamic-Simulation to estimate the inductance of a permanent magnet type transverse flux rotating motor by applying the real-time parameter estimation theory. As transverse flux rotating motor has the complex structure, it can be happen to some errors between real value and designed one with respect to the inductance. To reduce this kinds of errors, the real-time parameter estimation theory was applied to dynamic-simulation. And then, By comparing the estimated inductance and designed one, it is realized that the real-time parameter estimation theory can be applied in the permanent magnet type transverse flux rotating motor.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.352-355
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• 1995

In this paper, estimation error bounds of the optimal FIR (Finite Impulse Response) filter, which is proposed by Kwon et al.[1, 2], are presented in discrete-time systems with the model uncertainty. Performance bounds are here represented by the upper bounds on the difference of the estimation error covariances between the nominal and real values in case of the systems with the noise or model parameter uncertainty. The estimation error bounds of the discrete-time optimal FIR filter is compared with those of the Kalman filter via a numerical example applied to the simulation problem by Toda and Patel[3]. Simulation results show that the former has robuster performance than the latter.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.166-173
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• 2007

In this paper, we propose a model-based approach to estimating production parameters of semiconductor FAB equipment. For FAB scheduling, for example, we need to know equipment's production parameters such as flow time, tact time, setup time, and down time. However, these data are not available, and they have to be estimated from material move data such as loading times and unloading times that are automatically collected in modern automated semiconductor FAB. The proposed estimation method may be regarded as a Bayes estimation method because we use additional information about the production parameters. Namely, it is assumed that the technical ranges of production parameters are known. The proposed estimation method has been applied to a LCD FAB, and found to be valid and useful.

• 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.

• Journal of Power Electronics
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• v.16 no.1
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• pp.1-8
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• 2016

Dead time is typically incorporated in voltage source inverter systems to prevent short circuit cases. However, dead time causes an error between the output voltage and reference voltage. Hence, voltage equation-based algorithms, such as motor parameter estimation and back electromotive force (EMF)-based sensorless algorithms, are prone to estimation errors. Several dead-time compensation methods have been developed to reduce output voltage errors. However, voltage errors are still common in zero current crossing areas, and an effect of the error is much worse in a low speed region. Therefore, employing voltage equation-based algorithms in low speed regions is difficult. This study analyzes the conventional dead-time compensation method and output voltage errors in low speed operation areas. A current shaping method that can reduce output voltage errors is also proposed. Experimental results prove that the proposed method reduces voltage errors and improves the accuracy of the parameter estimation method and the performance of the back EMF-based sensorless algorithm.