• Journal of the Korean Statistical Society
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• v.4 no.1
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• pp.67-78
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• 1975

Over twenty-five years ago, Professor Klein and Rubin presented the linear expenditure system. That system was first estimated by Stone. Subsequently many investigators have estimated that system. In this paper, many points of the error structure shown by Pollak and Wales are referred to. Barten presented an estimation theorem on a singular covariance matrix. In order to estimate parameters, we place an emphasis on the maximum likihood method which we believe to be most appropriate. As we have one linear restriction on parameters to be estimated, we maximized the associated likelihood function subject to that linear restriction through the well-known lagrange multiplier method. This paper is organized in the following fashion : (1) a brief description on classical consumer theory, (2) a linear expenditure system and its constraint, (3) dyanmic specification and stochastic specification, (4) estimation method, and (5) conclusion.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.495-508
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• 2005

Moving objects are spatiotemporal data that change their location or shape continuously over time. Their location coordinates are periodically measured and stored i3l the application systems. The linear function is mainly used to estimate the location information that is not in the system at the query time point. However, a new method is needed to improve uncertainties of the location representation, because the location estimation by linear function induces the estimation error. This paper proposes an application method of the cubic spline interpolation in order to reduce deviation of the location estimation by linear function. First, we define location information of the moving object on the two-dimensional space. Next, we apply the cubic spline interpolation to location estimation of the proposed data model and describe algorithm of the estimation operation. Finally, the precision of this estimation operation model is experimented. The experimentation comes out more accurate results than the method by linear function.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.107-113
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• 2011

An OFDMA(Orthogonal Frequency Division Multiple Access) includes a MIMO(Multi-Input Multi-Output) scheme for improving spectral efficiency and data throughput. Recognizing that the performance of MIMO system is heavily dependent upon the accuracy of channel estimation, we propose a novel channel estimation for the MIMO scheme based on OFDMA. Conventional interpolation-based channel estimation suffers from poor estimation error at specific subcarriers. Proposed scheme makes use of a planar interpolation instead of linear interpolation for those subcarriers of bad accuracy. Simulation results show that the proposed scheme improves the performance of MIMO system by improving the accuracy in channel estimation especially for the adverse subcarrier positions. It is observed that the proposed scheme outperforms the conventional method by about 2dB in terms of both mean squared error and overall bit error rate with a reasonable computational complexity.

• ETRI Journal
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• v.31 no.6
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• pp.806-808
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• 2009

A new computationally efficient algorithm-based propagator method for two-dimensional (2-D) direction-of-arrival (DOA) estimation is proposed, which uses two parallel uniform linear arrays. The algorithm takes advantage of the special structure of the array which enables 2-D DOA estimation without pair matching. Simulation results show that the proposed algorithm achieves very accurate estimation at a computational cost 4 dB lower than that of standard methods.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.3
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• pp.399-406
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• 1996

This paper presents a method of hierarchical state estimation of the time-varying linear systems via Block-pulse function(BPF). When we estimate the state of the systems where noise is considered, it is very difficult to obtain the solutions because minimum error variance matrix having a form of matrix nonlinear differential equations is included in the filter gain calculation. Therefore, hierarchical approach is adapted to transpose matrix nonlinear differential equations to a sum of low order state space equation from and Block-pulse functions are used for solving each low order state space equation in the form of simple and recursive algebraic equation. We believe that presented methods are very attractive nd proper for state estimation of time-varying linear systems on account of its simplicity and computational convenience. (author). 13 refs., 10 figs.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.6
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• pp.487-491
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• 2008

Tuning of the speed controller in the linear servo applications needs the accurate information of a mover mass including a load mass. Therefore this paper proposes the mass estimation method of a permanent magnet linear synchronous motor(PMLSM) applied at the vertical axis by using the recursive Least-Squares estimation algorithm. First, this paper derives the deterministic autoregressive moving average(DARMA) model of the mechanical dynamic system used at the vertical axis. The application of the Least-Squares algorithm to the derived DARMA model gives the mass estimation method. Matlab/Simulink-based simulation and experimental results show that the total mover mass of a PMLSM applied at the vertical axis can be accurately estimated at both no-load and load conditions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.337-342
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• 2016

In this paper, we studied a modified linear prediction method to estimate target signal correctly. Linear prediction method estimate direction-of-arrival to linear combination for any antenna element and other antenna elements. Modified linear prediction used optimal weight and posterior probability method. Through simulation, we are comparative analysis about the performance of proposed, bartlett and MUSIC method. From simulation, Bartlett and MUSIC method was estimation 3 targets signal, and proposed method estimated 4 targets. We showed the superior performance of the proposed algorithm relative to the classical method in order to estimate of target signals.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.98-103
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• 1997

Given the small bit allocation for motion information in very low bit-rate coding, motion estimation using the block matching algorithm(BMA) fails to maintain an acceptable level of prediction errors. The reson is that the motion model, or spatial transformation, assumed in block matching cannot approximate the motion in the real world precisely with a small number of parameters. In order to overcome the drawback of the conventional block matching algorithm, several triangle-based methods which utilize triangular patches insead of blocks have been proposed. To estimate the motions of image sequences, these methods usually have been based on the combination of optical flow equation, affine transform, and iteration. But the compuataional cost of these methods is expensive. This paper presents a fast motion estimation algorithm using a multiple linear regression model to solve the defects of the BMA and the triange-based methods. After describing the basic 2-D triangle-based method, the details of the proposed multiple linear regression model are presented along with the motion estimation results from one standard video sequence, representative of MPEG-4 class A data. The simulationresuls show that in the proposed method, the average PSNR is improved about 1.24 dB in comparison with the BMA method, and the computational cost is reduced about 25% in comparison with the 2-D triangle-based method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.4
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• pp.1133-1145
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• 1996

A method is proposed to predict the deformed shape of the structure subjected to the unknown external loads using the signal from the piezoceramic sensors. Such a shape estimation is based on the linear relationship between the deformation of structure and the signal from sensor, which is calculated using finite element method. The deformed shape is, then calculated using the linear matrix and the signals from the piezoceramic sensors attached to the structures. For the purpose, a structural analysis program is developed using a multi-layerd finite element of 8 nodes with 3 displacement and one voltage degrees of freedom at each node. The multiple layers with the different material properties can be layered within the element. The incompatible mode with the element is found to be crucial to catch the bending behavior accurately. The accuracy of the program is, then, verified by being compared with the experimental results performed by Crawley. The proposed shape estimation method is also verified for the different loads and sensor size. It is shown that the results of shape estimation method using the linear matrix well predicts the deflections compared with those of finite element method.

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1341-1364
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• 2023

This article introduces a method for estimating the conditional hazard function of a real-valued response variable based on a functional variable. The method uses local linear estimation of the conditional density and cumulative distribution function and is applied to a functional stationary ergodic process where the explanatory variable is in a semi-metric space and the response is a scalar value. We also examine the uniform almost complete convergence of this estimation technique.