• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.569-572
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• 1999

In this paper we present a color image segmentation algorithm based on statistical models. A novel deterministic annealing Expectation Maximization(EM) formula is derived to estimate the parameters of the Gaussian Mixture Model(GMM) which represents the multi-colored objects statistically. The experimental results show that the proposed deterministic annealing EM is a global optimal solution for the ML parameter estimation and the image field is segmented efficiently by using the parameter estimates.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1079-1086
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• 2005

Most discussions of single imputation methods and the EM algorithm concern point estimation of population quantities with missing values. A second concern is how to get standard errors of the point estimates obtained from the filled-in data by single imputation methods and EM algorithm. Now we focus on how to estimate standard errors with incorporating the additional uncertainty due to nonresponse. There are some approaches to account for the additional uncertainty. The general two possible approaches are considered. One is the jackknife method of resampling methods. The other is multiple imputation(MI). These two approaches are reviewed and compared through simulation studies.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.97-98
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• 2008

전력계통이 커지고 복잡해짐에 따라 전력계통의 상태를 정확하게 파악하고 안정하게 운영하는데 EMS의 역할이 더욱 커지고 있다. EMS에서 상태추정은 다른 응용프로그램에 대한 기본 자료를 제공하므로 중요하다. 우리나라는 EMS와 MOS를 이용하여 전력계통을 안정하게 운영하고 있다. 본 논문에서는 EMS와 MOS의 상태추정 알고리즘을 소개하고 차이점을 비교하였다. 또한 상태추정 파라미터 운영현황을 분석하여 이를 바탕으로 앞으로의 개선방향을 제시하였다.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.165-173
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• 2018

Underwater vehicles use Inertial Navigation System (INS) with high-performance Inertial Measurement Unit (IMU) for high precision navigation. However, when underwater navigation is performed for a long time, the INS error gradually diverges, therefore, an integrated navigation method using auxiliary sensors is used to solve this problem. In terms of underwater vehicles, the vertical axis error is primarily compensated through Vertical Channel Damping (VCD) using a depth gauge, and an integrated navigation filter can be designed to perform horizontal axis error and sensor error correction using a speedometer such as Electromagnetic-Log (EM-Log). However, since EM-Log outputs the forward direction relative speed of the vehicle with respect to the sea and sea current, INS correction filter using this may cause a rather large error. Although it is possible to design proper filters if the exact model of the sea current is known, it is impossible to know the accurate model in reality. Therefore, this study proposes an INS/EM-Log integrated navigation filter with the function to estimate sea current using an Interacting Multiple Model (IMM) filters, and the performance of this filter is analyzed through a simulation performed in various environments.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.156-162
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• 2016

For the underwater localization, acoustic sensor systems are widely used due to greater penetration properties of acoustic signals in underwater environments. On the other hand, the good penetration property causes multipath and interference effects in structured environment too. To overcome this demerit, a localization method using the attenuation of electro-magnetic(EM) waves was proposed in several literatures, in which distance estimation and 2D-localization experiments show remarkable results. However, in 3D-localization application, the estimation difficulties increase due to the nonuniform (doughnut like) radiation pattern of an omni-directional antenna related to the depth direction. For solving this problem, we added a depth sensor for improving underwater 3D-localization with the EM wave method. A micro scale pressure sensor is located in the mobile node antenna, and the depth data from the pressure sensor is calibrated by the curve fitting algorithm. We adapted the depth(z) data to 3D EM wave pattern model for the error reduction of the localization. Finally, some experiments were executed for 3D localization with the fast calculation and less errors.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.691-697
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• 2015

In this paper, an embedded EM sensor was researched to estimate prestressing force of PS tendon in PSC girder. Recent methodologies for managing prestressing force loss were staying on verifying a applying prestressing force under construction, namely the loss management can not be controlled after construction. To estimate the tensile force of PS tendon during lifetime of PSC girder, this research proposed a bobbin-type embedded EM sensor that can be embedded in PSC girder is designed and fabricated considering the shape properties of anchorage zone and sheath. To verify the proposed sensor, a small PSC girder test was performed. The embedded EM sensor was connected to a sheath and anchor block, and the concrete was poured. After curing, the change of the permeability of PS tendon under tensile forces of 200, 710, 1070, 1300kN was measured using embedded EM sensor. The permeability of PS tendon had decreased according to the increment of applied tensile force. Also it is confirmed that the change of permeability due to applied tensile force could resolve the applied tensile force values. As a result, proposed embedded EM sensor could be embed into the PSC girder and it could be used to estimate the tensile force variation during lifetime of PSC girder.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.255-261
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• 2014

Many studies have estimated a mixture of binomial distributions. This paper considers an extension, a mixture of shifted binomial distributions, and the estimation of the distribution. The range of each component binomial distribution is rst evaluated and then for each possible value of shifted parameters, the EM algorithm is employed to estimate those parameters. From a set of possible value of shifted parameters and corresponding estimated parameters of the distribution, the likelihood of given data is determined. The simulation results verify the performance of the proposed method.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.795-804
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• 2003

In this article, a tomography for the estimation of the origin-destination(OD) traffic intensities in dynamic routing network is considered. Vardi(1996)'s approach based on fixed route is not directly applicable to dynamic routing protocols, which arises from the fact that we cannot access the route at every observation time. While it uses link-wise traffics as the observations, the proposed method considers the triple of ingress/outgress/relayed traffics data at each node so that we can transform the problem into a routing-independent tomography. An EM algorithm for implementation and some simulated experiments are provided.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2615-2617
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• 2003

The Kalman filter is a recursive Linear Estimator for the linear dynamic systems(LDS) affected by two different noises called process noise and measurement noise both of which are uncorrelated white. The Expectation Maximization(EM) algorithm is employed in this paper as a preprocessor to reinforce the effectiveness of Kalman estimator. Particularly, we focus on the relation between Kalman filter and EM algorithm in the LDS. In this paper, we propose a new algorithm to improve the performance on the parameter estimation via EM algorithm, which improves the overall process of Kalman filtering. Since Kalman filter algorithm not only needs the system parameters but also is very sensitive the initial state conditions, the initial conditions decided through EM turns out to be very effective. In experiments, the computer simulation results ate provided to demonstrate the superiority of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1154-1163
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• 2007

For orthogonal frequency division multiplexing (OFDM), cyclic prefix (CP) should be longer than the length of channel impulse response. In order to prevent a loss of bandwidth efficiency due to the use of a CP, residual intersymbol interference cancellation (RISIC) method has recently been developed. In this paper, we first apply the RISIC algorithm to the space-time block coded (STBC) OFDM and the space-frequency block coded (SFBC) OFDM with insufficient CP. It is shown that in the STBC OFDM, tail cancellation as well as cyclic restoration of the RISIC should be repeated. Second, we propose iterative channel estimation method for the RISIC in the STBC OFDM system with insufficient CP. Based on the expectation-maximization (EM) algorithm, the proposed estimation method exploits the extrinsic probabilities of the channel decoder iteratively. The performance of the proposed method is evaluated by computer simulation in a multipath fading environment.