• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.526-526
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• 2000

The present has a double objective. The first one is to compare and estimate sixteen continuous-time methods through the identificatiun of a system consisted with an RLC electrical circuit. These sixteen methods are classified into three groups that are the linear filters, the modulating functions and the integral methods. The second objective is to estimate directly the physical parameters of the RLC circuit, without resorting to a discrete-time model. The system is consisted of a coil with inductance L and resistance H, and of a capacitor with capacitance C. Having written the physical equations which describe the behavior of the system, the transfer function in where the initial conditions appear is given. These initial conditions should be taken into account during the parameter estimation phase, because they are inevitable within the framework of real signals. A physical interpretation of the identified models is tempted by the direct estimation of the physical parameters L and C. In conclusion, a classification of the studied methods is proposed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.26-32
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• 1994

The Lloyd-Max algorithm is an iterative scheme for design of the minimum mean square error quantizer. It is very simple in concept and easy to program into a computer. However its convergence and accuracy are primarily dependent upon the accuracy of the initial parameter. In this paper, a new initial parameter which converges to a specific value when the number of output levels becomes large is selected. And an estimator using curve fitting techique is suggested. In addition, performance of the proposed method is shown to be superior to that of the existing methods in accuracy and convergence.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.153-160
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• 2004

In recent years, the size of data set which we usually handle is enormous, so a lot of outliers could be included in data set. Therefore the robust procedures that automatically handle outliers become very importance issue. We consider the robust estimation problem of location parameter in the univariate case. In this paper, we propose a new method for defining robustness weights for the weighted mean based on the median distance of observations and compare its performance with several existing robust estimators by a simulation study. It turns out that the proposed method is very competitive.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.71-76
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• 1998

By assuming a general progressive Type-II censored sample, we propose the minimum risk estimator (MRE) of the location parameter and the scale parameter of the two-parameter exponential distribution. An example is given to illustrate the methods of estimation discussed in this paper.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.413-423
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• 2005

Consider the problem of estimating the underlying regression function from a set of noisy data which is contaminated by a long tailed error distribution. There exist several robust smoothing techniques and these are turned out to be very useful to reduce the influence of outlying observations. However, no matter what kind of robust smoother we use, we should choose the smoothing parameter and relatively less attention has been made for the robust bandwidth selection method. In this paper, we adopt the idea of robust location parameter estimation technique and propose the robust cross validation score functions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.10a
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• pp.175-182
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• 1994

As for the safety evaluation of existing large-scale structures, methods for estimation of the structural and dynamic properties are studied. Sequential prediction error method in time domain and improved FRF estimator in frequency domain are comparatively studied. For this purpose, impact tests of 2 bay 3 floor steel frame structure are performed. Results from both methods are found to be consistent to each others, however those from the finite-element analysis are slightly different from experimental results.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.215-218
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• 2000

In this paper, a new algorithm for adaptive IIR filters based on equation error methods using the RLS algorithm is proposed. In the proposed algorithm, the concept of feedback of the scaled output error proposed by tin and Unbehauen is employed and the forgetting factor is varied in adaptation process for avoiding the accumulation of the estimation error for additive noise . The proposed algorithm has the good convergence property without the parameter estimation error under the existence of mea-surement noise.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.7-13
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• 2012

This paper is to estimate aerodynamic coefficients needed to determine the missiles' controller design and stability from simulation data of Skid-to-Turn missile. Method of determining aerodynamic coefficients is to apply Neural Network and Recursive Least Square and results were compared and researched. Also analysing actual flight test data was considered and sensor noise was added. Estimate parameter of data with sensor noise added and estimated performance and reliability for both methods that did not need initial values. Both Neural Network and Recursive Least Square methods showed excellent estimate results without adding the noise and with noise added Neural Network method showed better estimate results.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.187-188
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• 2011

This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.1
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• pp.11-19
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• 2010

Register transfer level power macromodeling is well known as a promising technique for accurate and efficient power estimation. This paper proposes effective approaches based on the tablebased method for the RTL power macro-modeling. The new parameter SD, which characterizes the distribution of switching activities for each gate in the circuit, is one of the contributions. The new parameter SD has strong correlation with power consumption. We also propose an accurate table reference method considering the circuit characteristics. The table reference method is applicable for every table-based method and outputs more accurate power value. The experimental results show that the combination of the proposed methods reduces max error 30.36% in the best case, comparing conventional methods. The RMS error is also improved 1.70% in the best case.