• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.105-112
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• 2002

In this paper we establish bivariate exponentially weighted moving average (EWMA) control charts for autocorrelated processes using residual vectors. We first derive the residual vectors, their expectation, variance-covariance matrix, then evaluate the control chart based on the average run length (ARL).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.11 no.4
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• pp.133-141
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• 1991

The empirical method is used to integration adjustment for the coordinates revision of a national control point but the existing values are not to be changed or changed with small variation by suitable datum selection (for example, fixed points). This paper treats the modified weighted station parameter adjustment by quasi-observations, and the method used only variance elements of existing coordinates which is substituted for all covariance elements. The movement detection of unstable points and the junction adjustment of new networks are successfully executed by the method, in integration of new secondary networks to old-secondary-triangulation points which are in the absence of the original observations in Korea. The investigation results reveal that the accuracy of old-secondary-triangulation points is ${\pm}16^{{\prime}{\prime}}$(${\pm}0.08m$), which results from the densification of test network and the analyses of old survey specifications. and is ${\pm}2.3^{{\prime}{\prime}}$ in fixing of old-secondary-triangulation points.

• MALSORI
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• no.53
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• pp.103-118
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• 2005

The performance of speech recognition system is degraded by mismatch between training and test environments. Recently, Stereo-based Piecewise LInear Compensation for Environments (SPLICE) was introduced to overcome environmental mismatch using stereo data. In this paper, we propose several methods to improve the conventional SPLICE and evaluate them in the Aurora2 task. We generalize SPLICE to compensate for covariance matrix as well as mean vector in the feature space, and thereby yielding the error rate reduction of 48.93%. We also employ the weighted sum of correction vectors using posterior probabilities of all Gaussians, and the error rate reduction of 48.62% is achieved. With the combination of the above two methods, the error rate is reduced by 49.61% from the Aurora2 baseline system.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.873-883
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• 2016

In this paper, we focus on maximizing weighted sum energy efficiency (EE) for a multi-cell multi-user channel. In order to solve this non-convex problem, we first decompose the original problem into a sequence of parallel subproblems which can optimized separately. For each subproblem, a base station employs dirty paper coding to maximize the EE for users within a cell while regulating interference induced to other cells. Since each subproblem can be transformed to a convex multiple-access channel problem, the proposed method provides a closed-form solution for power allocation. Then, based on the derived optimal covariance matrix for each subproblem, a local optimal solution is obtained to maximize the sum EE. Finally, simulation results show that our algorithm based on non-linear precoding achieves about 20 percent performance gains over the conventional linear precoding method.

• International Journal of Contents
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• v.15 no.4
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• pp.27-35
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• 2019

In this paper, we propose an advanced Minimum Mean Square Error (MMSE) channel estimation method for IEEE 802.11p/Wireless Access in Vehicular Environments (WAVE) systems. To improve the performance of MMSE method, we apply the Weighted Sum using Update Matrix (WSUM) scheme to the step of calculating the instantaneously estimated channel and then, a time domain selectively averaging method is applied after the WSUM scheme. Based on that, the accuracy of instantaneously estimated channel increases and then, the accuracy of auto covariance matrix also increases. Consequently, we can achieve the performance gain over the conventional MMSE method. Through simulations based on the IEEE 802.11p standard, it is confirmed that the proposed scheme can outperform the existing channel estimation schemes.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.11
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• pp.1207-1218
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• 1990

The lack of persistent excitation (PE) can be the reason of freezing in the recursive least square estimators and the covariance windup in the exponential weighted least square estimators. We present a theoretical analysis of these phenomena and a simple method to check the exciting condition in real time. Using these results and under some conditions such as slowly time varying Plant and a tracking problem for set point, a robust self-tuning regulators without PE is proposed. In this algorithm, when PE is not satisfied, only plant gain is estimated, and then the system parameters are corrected by it. It is shown that the gain adaptive scheme makes the robustness to be improved against modeling error, off-set, and correlated noise etc, by the results of analysis and simulations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.11-18
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• 1998

In this paper the stochastic analysis of semi-infinite domain is presented using the weighted integral method, which is expanded to include the infinite finite elements. The semi-infinite domain can be thought as to have more uncertainties than the ordinary finite domain in material constants, which shows the needs of and the importance of the stochastic finite element analysis. The Bettess's infinite element is adopted with the theoretical decomposition of the strain matrix to calculate the deviatoric stiffness of the semi-infinite domains. The calculated value of mean and the covariance of the displacement are revealed to be larger than those given by the finite domain assumptions giving the rational results which should be considered in the design of structures on semi-infinite domains.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.109-120
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• 2015

Spatial heterogeneous characteristics of solar radiation energy from Climate Change gives rise to energy imbalance in the general ecological system including water resources. This study is to estimate the $CO_2$ flux of South Korea using Terra MODIS image and to assess the reliability of MODIS data from the ground measured $CO_2$ flux by eddy covariance flux tower data at 3 locations (two at mixed forest area and one at rice paddy area). The MODIS Gross Primary Productivity (GPP) product (MOD17A2), 8-day composite at 1-km spatial resolution was adopted for the spatial $CO_2$ flux generation. The MOD17A2 data by noise like cloud and snow in a day were tried to fill by Inverse Distance Weighted (IDW) method from valid pixels and the damping effect of MOD17A2 data were corrected by Quality Control (QC) flag. The MODIS $CO_2$ flux was estimated as the sum of GPP and Re (ecosystem respiration) by Lloyd and Taylor method (1994). The determination coefficient ($R^2$) between MODIS $CO_2$ and flux tower $CO_2$ for 3 years (2011~2013) showed 0.55 and 0.60 in 2 mixed forests and 0.56 in rice paddy respectively. The $CO_2$ flux generally fluctuated showing minus values during summer rainy season (from July to August) and maintaining plus values for other periods. The MODIS $CO_2$ flux can be a useful information for extensive area, for example, as a reliable indicator on ecological circulation system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.445-458
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• 2012

The objective of GPS control surveying is ultimately to determine coordinate sets of control points within targeted accuracy through a series of observations and network adjustments. To this end, it is of equivalent importance for the accuracy of these coordinates to be realistically represented by using an appropriate method. The accuracy representation can be quantitively made by the variance-covariance matrices of the estimates, of which features are sensitive to the mathematical models used in the adjustment. This paper deals with impact of functional and stochastic modeling techniques into the accuracy representation of the GPS control surveying with a view of gaining background for its standardization. In order to achieve this goal, mathematical theory and procedure of the single-baseline based multi-session adjustment has been rigorously reviewed together with numerical analysis through processing real world data. Based on this study, it was possible to draw a conclusion that weighted-constrained adjustment with the empirical stochastic model was among the best scheme to more realistically describe both of the absolute and relative accuracies of the GPS surveying results.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.229-250
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• 2022

Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.