• Atmosphere
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• v.32 no.4
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• pp.263-276
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• 2022

The observation error of satellite radiation data that assimilated into the Korean Integrated Model (KIM) was diagnosed by applying the Hollingsworth and Lönnberg and Desrozier techniques commonly used. The magnitude and correlation of the observation error, and the degree of contribution for the satellite radiance data were calculated. The observation errors of the similar device, such as Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit-A shows different characteristics. The model resolution accounts for only 1% of the observation error, and seasonal variation is not significant factor, either. The observation error used in the KIM is amplified by 3-8 times compared to the diagnosed value or standard deviation of first-guess departures. The new inflation value was calculated based on the correlation between channels and the ratio of background error and observation error. As a result of performing the model sensitivity evaluation by applying the newly inflated observation error of ATMS, the error of temperature and water vapor analysis field were decreased. And temperature and water vapor forecast field have been significantly improved, so the accuracy of precipitation prediction has also been increased by 1.7% on average in Asia especially.

• Journal of the Korea Society for Simulation
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• v.10 no.4
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• pp.41-50
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• 2001

When optimizing a complex system by determining the optimum condition of the system parameters of interest, we often employ the process of estimating the unknown objective function, which is assumed to be a second order spline function. In doing so, we normally use common random numbers for different set of the controllable factors resulting in more accurate parameter estimation for the objective function. In this paper, we will show some mathematical result for the analysis of variance when using common random numbers in terms of the regression error, the residual error and the pure error terms. In fact, if we can realize the special structure of the covariance matrix of the error terms, we can use the result of analysis of variance for the uncorrelated experiments only by applying minor changes.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1124-1129
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• 2006

In this paper, in-flight alignment algorithm using UKF is presented for an SDINS aided by SSBL or GPS system under large initial heading error. The EKF usually applied for this task. This approximates the propagation of mean and covariance accurate to first-order only. To overcome this limitation, the unscented transformation that achieves second order approximation is applied to the in-flight alignment. To analyze the performance of the proposed method, simulations for S-type trajectory are carried out. The results show that performance of EKF and UKF are the almost same when the initial heading error is smaller than $30^{\circ}$, but UKF has a better performance for large initial heading error about $45^{\circ}$.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.2
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• pp.114-125
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• 2003

This paper proposes multivariate process capability indices (PCIs) for skewed populations using $T^2$rand modified process region approaches. The proposed methods are based on the multivariate version of a weighted standard deviation method which adjusts the variance-covariance matrix of quality characteristics and approximates the probability density function using several multivariate Journal distributions with the adjusted variance-covariance matrix. Performance of the proposed PCIs is investigated using Monte Carlo simulation, and finite sample properties of the estimators are studied by means of relative bias and mean square error.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.3
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• pp.52-56
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• 1980

The Signal -to- Noise Ratio of delta modulation for a fi rEt -order Gauss -Markov signal is derived and an approximate expreession of SND is discussed, in the case that only granular noise arises. Cross covariance of input and error signals are negligible when the adjacent correlation of input signal is larger than the difference between the adjacent correlation and the prediction coefficient of local decoder. The approximately derived SNR is available for any value of adjacent correlation.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.701-718
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• 2006

In cancer microarray experiments, the experimenter or patient which is nested in each experimenter often shows quite heterogeneous error variability, which should be estimated for identifying a source of variation. Our study describes a Bayesian method which utilizes clinical information for identifying a set of DE genes for the class of subtypes as well as assesses and examines the experimenter effect and patient effect which is nested in each experimenter as a source of variation. We propose a Bayesian multilevel mixed effect model based on analysis of covariance (ANACOVA). The Bayesian multilevel mixed effect model is a combination of the multilevel mixed effect model and the Bayesian hierarchical model, which provides a flexible way of defining a suitable correlation structure among genes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.459-464
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• 2001

We propose a transmit beamforming algerian for array antenna in FDD (Frequency Division Duplex) environments. The proposed method estimates the directions and spectra of the users, and constructs the spatial covariance matrix of the interferences at the downlink frequency. The weights are computed by that covariance matrix and desired user's direction vector Simulations are performed under Rayleigh fading environments. The proposed method don't need the data feedback, has the enhanced performance in BER (Bit Error Rate).

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.87-100
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• 2002

Poorly-posed problems in the balanced discriminant analysis was considered. We restrict consideration to the case of observations and the number of variables are the same and small. When these problems exist, we do not use a maximum likelihood estimates(MLE) to estimate covariance matrices. Instead of MLE, an alternative estimate for the covariance matrices are proposed. This alternative method make good use of two regularization parameters, $\lambda$} and $\gamma$. A new test rule for the discriminant function is suggested and examined via limited hut informative simulation study. From the simulation study, it is shown that the suggested test rule gives better test result than other previously suggested method in terms of error rate criterion.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.410-417
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• 2003

In this paper, We propose a new target tracking filter which utilizes PDA-AI for data association in a clutter environment and also propose an analytic solution for ideal filter covariance which accounts for all the possible events in PDA-AI. Monte Carlo simulation for the proposed filter in a clutter environment indicates that the proposed analytic solution forms a tight lower bound for the error covariance of PDA-AI filter.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.54-55
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• 2015

In this paper, we propose a method pursuing robustness in ad hoc network system when the CSI of interferers is unavailable. The non-parametric linear minimum mean square error filter is exploited to achieve large fraction of the MMSE filter transmission capacity employing the perfect covariance matrix information. From the numerical results, we show that the proposed scheme brings substantial transmission capacity gain over conventional MMSE filter using sample covariance matrix.