• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.87-90
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• 1988

This paper reports a simple posteriori error estimate method for adaptive finite element mesh generation using quadratic shape function especially for the magnetic field problems. The elements of quadratic shape function have more precise solution than those of linear shape function. Therefore, the difference of two solutions gives error quantity. The method uses the magnetic flux density error as a basis for refinement. This estimator is tested on two dimensional problem which has singular points. The estimated error is always under estimated but in same order as exact error, and this method is much simpler and more convenient than other methods. The result shows that the adaptive mesh gives even better rate of convergence in global error than the uniform mesh.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.177-183
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• 1997

A data-adaptive order selection procedure is proposed for local polynomial nonparametric regression. For each given polynomial order, bias and variance are estimated and the adaptive polynomial order that has the smallest estimated mean squared error is selected locally at each location point. To estimate mean squared error, empirical bias estimate of Ruppert (1995) and local polynomial variance estimate of Ruppert, Wand, Wand, Holst and Hossjer (1995) are used. Since the proposed method does not require fitting polynomial model of order higher than the model order, it is simpler than the order selection method proposed by Fan and Gijbels (1995b).

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.501-508
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• 2003

Although the estimate of regression function is important, some have focused the variance estimation of error term in regression model. Different variance estimators perform well under different conditions. In many practical situations, it is rather hard to assess which conditions are approximately satisfied so as to identify the best variance estimator for the given data. In this article, we suggest SHM estimator compared to LS estimator, which is common estimator using in parametric multiple regression analysis. Moreover, a combined estimator of variance, VEM, is suggested. In the simulation study it is shown that VEM performs well in practice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1792-1801
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• 2012

Symbol timing error amounts to a major degradation in the system performance. Conventionally, timing error is estimated by predefined preamble on both transmitter and receiver. The maximum of the correlation result is considered the start of the OFDM symbol. Problem arises when the prime path is not the strongest one. In this paper, we propose a new combined time and channel estimation method for multi-band OFDM ultra wide-band (MB-OFDM UWB) systems. It is assumed that a coarse timing has been obtained at a stage before the proposed scheme. Based on the coarse timing, search interval is set (or time candidates). Exploiting channel statistics that are assumed to be known by the receiver, we derive a maximum a posteriori estimate (MAP) of the channel impulse response. Based on this estimate, we discern for the timing error. Timing estimation performance is compared with the least squares (LS) channel estimate in terms of mean squared error (MSE). It is shown that the proposed timing scheme is lower in MSE than the LS method.

• Publications of The Korean Astronomical Society
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• v.9 no.1
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• pp.55-68
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• 1994

We have reviewed three different techniques to estimate molecular cloud mass, and discussed the uncertainties involved. We found that determination of the most important parameter, the $^{13}CO$ abundance, is not very sensitive to the real LTE conditions, and that any possible error in deriving LTE column density may not introduce an error in the total gas column density, as far as the visual extinction is established for the object cloud. The virial technique always endows the largest mass estimate as there are several uncertainties, even if the cloud is in virial equilibrium. The strong indicator of the cloud perturbation is the centroid velocity dispersion. The mass using CO luminosity is based on the empirical law, but weakly dependent on the virial assumption, thus it still gives a larger mass estimate. The mass discrepancy is likely to be inevitable, and a factor of two or three difference between mass estimates could easily be attributed to the uncertainties mentioned above. The LTE mass estimate may be the most reliable one if we use the relation visual extinction and $^{13}CO$ column density of the object cloud, and the intercept is included.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.51-58
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• 2002

Vehicle dynamics control systems are. complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed is good results in normal conditions. But the estimation error in severe braking is discontented. In this paper, we estimate the absolute vehicle speed by using the wheel speed data from standard 50-tooth anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used. Ten algorithms are verified experimentally to estimate the absolute vehicle speed and one of those is perfectly shown to estimate the vehicle speed with a 4% error during a braking maneuver.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.415-421
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• 2009

TOA(time-of-arrival) and TDOA(time-difference-of-arrival) positioning techniques are commonly used in many radio-navigation systems. From the literature, it is known that the position estimate and error covariance matrix of TDOA obtained by GN(Gauss-Newton) method is exactly the same as that of TOA when the error source of the range measurement is only an IID white Gaussian noise. In case of geo-location and indoor positioning, however, multi-path or NLOS(non-line-of-sight) error is frequently appeared in range measurements. Though its occurrence is random, the multipath acts like a bias for a stationary user if it occurs. This paper presents the comparisons of error characteristics between TOA and TDOA positioning in presence of multi-path or NLOS error. It is analytically shown that the position estimate of TDOA is exactly the same as that of TOA even when bias errors are included in range measurements with different magnitudes. By computer simulation, position estimation error and error distribution are analyzed in presence of range bias errors.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.61-82
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• 2000

In this paper two so-called regularized Green's functions are introduced to derive the optimal maximum norm error estimates for the unknown function and the adjoint vector-valued function for mixed finite element methods of Laplacian operator. One contribution of the paper is a demonstration of how the boundedness of $L^1$-norm estimate for the second Green's function ${\lambda}_2$ and the optimal maximum norm error estimate for the adjoint vector-valued function are proved. These results are seemed to be to be new in the literature of the mixed finite element methods.

• The Korean Journal of Physiology and Pharmacology
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• v.16 no.2
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• pp.97-106
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• 2012

The pharmacokinetics/pharmacodynamics analysis software NONMEM$^{(R)}$ output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM$^{(R)}$ VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.1 s.24
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• pp.99-108
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• 2006

In this paper, we analyzed the characteristics of emitter geolocation coverage area within which the emitter lies with a specified probability based on the LOBs(Line of Bearing) of sensors. Stansfield and MSD algorithms were applied to calculate BPE(Best Point Estimate), EEP(Elliptical Error Probable) and CEP(Circular Error Probable), They used the weighting factors composed of ${\sigma}_{Phi}$ (bearing error), QF(quality factor), $P_{e}$ (probability being inside) to optimize the performance. The characteristics of EEP was investigated in the change of them and those of CEP was analyzed based on the deployment of sensors.