• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.397-402
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• 2009

Accurate estimation of time-selective fading channel is a difficult problem in OFDM(Orthogonal Frequency Division Multiplexing) system. There are many channel estimation algorithms that are very weak in noisy channel. For solving this problem, we use EM (Expectation-Maximization) algorithm for iterative optimization of the data. We propose an EM-LPC algorithm to estimate the time-selective fading. The proposed algorithm improves of the BER performance compared to EM based channel estimation algorithm and reduces the iteration number of the EM loop. We simulated the uncoded system. If coded system use the EM-LPC algorithm, the performance are enhanced because of the coding gain. The EM-LPC algorithm is able to apply to another communication system, not only OFDM systems. The image processing of the medical instruments that the demand of accurate estimation can also use the proposed algorithm.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.68-77
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• 2002

EM algorithm has good convergence rate for numerical procedures which converges on very small step. In the case of proportion estimation in a mixed distribution which has very big incomplete data or of update of new data continuously, however, EM algorithm highly depends on a initial value with slow convergence ratio. There have been many studies to improve the convergence rate of EM algorithm in estimating the proportion parameter of a mixed data. Among them, dynamic EM algorithm by Hurray Jorgensen and Titterington algorithm by D. M. Titterington are proven to have better convergence rate than the standard EM algorithm, when a new data is continuously updated. In this paper we suggest dynamic EM algorithm and Titterington algorithm for the estimation of a mixed Poisson distribution and compare them in terms of convergence rate by using a simulation method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.35-47
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• 2023

Various single probability distributions have been used to represent time headway distributions. However, it has often been difficult to explain the time headway distribution as a single probability distribution on site. This study used the EM algorithm, which is one of the maximum likelihood estimations, for the parameters of combined mixture distributions with a certain relationship between two normal distributions for the time headway of vehicles. The time headway distribution of vehicle arrival is difficult to represent well with previously known single probability distributions. But as a result of this analysis, it can be represented by estimating the parameters of the mixture probability distribution using the EM algorithm. The result of a goodness-of-fit test was statistically significant at a significance level of 1%, which proves the reliability of parameter estimation of the mixture probability distribution using the EM algorithm.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.369-374
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• 2015

In this paper, an EM sensing based prestressing force estimation method is proposed, in which it can estimate tensile force of PS tendon for PSC girder. The PSC girder has more improved performance than the general concrete girder by introducing the prestressing to the concrete. Thus the PSC girder bridge is widely constructed due to its high performance and low cost. However, the prestressing force has not been managed nevertheless it is major factor for the maintenance of the PSC girder bridge. The prestressing force was just measured during construction using jacking device and after that, it can not be managed. For this reason, this paper proposes a tensile force estimation method of PS tendon based on EM sensor. The permeability of ferroelectric material is changed according to the induced stress to the material, in which it can be measured using EM sensor. To measure the permeability of PS tendon, the EM sensor was fabricated and verified by performing the MTS test. The test was performed using 7-wire steel tendon under the 0, 40, 80, 120, 160, 200 KN of tensile force. The permeability of PS tendon was gradually decreased according to the increasement of tensile force. The regression method was used to find the relation between permeability and stress. As a result, the permeability has linear relation with the tensile force of PS tendon and the pre-stressing force can be estimated by the derived estimation equation.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.145-157
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• 1994

For multivariate distributions satisfying stochastic ordering, we suggest maximum likelihood estimation with incomplete data via an EM algorithm. In this paper we restrict our attention to the contingency tables with partially cross-classified observations. We may use the existing isotonic regression program to implement EM algorithm, and we illustrate the estimation process through an example.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.785-794
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• 2006

Suggested is an EM algorithm for estimation in mixture of shifted Poisson distributions with known shift parameters. For this type of mixture distribution, we have to utilize values of shift parameters to determine whether each of data belongs to some component distribution. We propose a method of estimating values of component information and then follow typical EM methodology. Simulation results show that the algorithm provides reasonable performance for the distribution.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2E
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• pp.68-75
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• 1994

In many applications of signal processing, we have to deal with densities which are highly non-Gaussian or which may have Gaussian shape in the middle but have potent deviations in the tails. To fight against these deviations, we consider a finite mixture distribution for the speech excitation. We utilize the EM algorithm for the estimation of speech parameters and their enhancement. Robust Kalman filtering is used in the enhancement process, and a detection/estimation technique is used for parameter estimation. Experimental results show that the proposed algorithm performs better in adverse SNR input conditions.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1209-1217
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• 2006

For the mixture of shifted Poisson distributions, a method of parameter estimation is proposed. The range of the shifted parameters are estimated first and for each shifted parameter set EM algorithm is applied to estimate the other parameters of the distribution. Among the estimated parameter sets, one with minimum likelihood for given data is to be set as the final estimate. In simulation experiments, the suggested estimation method shows to have a good performance.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.675-677
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• 2005

This study proposes a fuzzy classification using EM algorithm. For cluster validation, this approach iteratively estimates the class-parameters in the fuzzy training for the sample classes and continuously computes the log-likelihood ratio of two consecutive class-numbers. The maximum ratio rule is applied to determine the optimal number of classes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.635-643
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• 2007

In this paper, a decision-directed expectation maximization (DEM) algorithm is proposed to improve the performance of channel estimation in OFDM-based cellular systems. The DEM algorithm enables a mobile station (MS) with multiple antennas, located at the cell boundary, to increase the performance of channel estimation using transmit data, without decreasing spectral efficiency. Also, DEM algorithm can apply fast fading without loss of channel estimation performance because that includes channel variation factor in a group. It is verified by computer simulation that the DEM algorithm can reduce computational complexity significantly while improving the performance of channel estimation in fast fading channels, compared with the expectation maximization (EM) algorithm.