• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.865-872
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• 2017

Recent advance in electronics and scintillators makes it possible to utilize the time-of-flight (TOF) information in improving image reconstruction of positron emission tomography(PET). In this paper, we propose a TOF-based fast image reconstruction method for PET. The proposed method uses the deconvolution of TOF data for each angle view and the rotational averaging of deconvolved images. Simulation results show an improved performance of the proposed method, as compared with filtered backprojection (FBP) method, TOF-FBP, and TOF version of expectation-maximization(EM) methods. Simulation results also show a great potentiality of the proposed method in limited angle tomography applications.

• Speech Sciences
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• v.15 no.3
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• pp.7-15
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• 2008

This paper proposes the method to extract new feature vectors using the difference between the cepstrum for static characteristics and delta cepstrum for dynamic characteristics in speaker recognition (SR). The difference vector (DV) which it proposes from this paper is containing the static and the dynamic characteristics simultaneously at the intermediate characteristic vector which uses the deference between the static and the dynamic characteristics and as the characteristic vector which is new there is a possibility of doing. Compared to the conventional method, the proposed method can achieve new feature vector without increasing of new parameter, but only need the calculation process for the difference between the cepstrum and delta cepstrum. Experimental results show that the proposed method has a good performance more than 2.03%, on average, compared with conventional method in speaker identification (SI).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8A
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• pp.1156-1162
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• 1999

In this paper, the problem of decoding transmitted data sequence with diversity reception in the presence of nondelective fading is studied. The expection maximizaton (EM) algorithm is employed to derive an interactive algorithm. The algorithm performs block-by-block coherent decoding with the aid of pilot symbols. It is shown that the complexity of the algorithm grows linearly as a function of sequence length. The performance of the algorithm is shown to better than that of the conventional pilot symbol aided (PSI) algorithm. Simulation results are presented to assess the performance of the algorithm and the results are compared with that of the conventional PSI alforithm.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.26 no.2
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• pp.151-157
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• 2013

In this paper, properties of pattern using LBG (Linde-Buzo-Gray) Algorithm was explored including the exactness of K-means algorithm and process time of EM (Expectation Maximization) algorithm in order to develop analysis algorithm of partial discharge pattern in a cable using acoustic data analysis system. Partial discharge was measured by generating inner fault due to lamination of XLPE which is used for cable insulation material. Discharge pattern was analysed by changing the number of swarm article to 2, 4, and 6 in order to interpret swarm structure and properties.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.110.1-110
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• 2002

We propose a novel neuro-fuzzy system based on an efficient clustering method. It is a very useful method that improves the performance of a fuzzy model with small number of fuzzy rules. The fuzzy clustering methods are studied in the wide range of fuzzy modeling. One of them, the grid partition method has problem of exponentially increasing number of rules when the dimension of input or number of membership function is linearly increased. On the other hand, the Expectation Maximization algorithm is an efficient estimation for unknown parameters of the Gaussian mixture model. Here it is noted that the parameters can be used for fuzzy clustering method. In a fuzzy modeling, it is desired that...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.96.2-96
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• 2002

In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme that represents the information from observations as a set of random variables in the form of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other, which can be utilized in linear p...

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.381-384
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• 2000

This paper proposes a method of estimating the lifetime distribution at use condition for constant stress accelerated lift tests when extrinsic failure mode as well as intrinsic one exists. A mixture of two log-normal distributions is introduced to describe these failure modes and it is assumed that a linear relation exists between the location parameter and stress. An estimation procedure using the expectation and maximization algorithm is proposed and a numerical example is given.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.167-170
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• 2003

We develop semiparametric methods for matched case-control studies using regression splines. Three methods are developed: an approximate crossvalidation scheme to estimate the smoothing parameter inherent in regression splines, as well as Monte Carlo Expectation Maximization (MCEM) and Bayesian methods to fit the regression spline model. We compare the approximate cross-validation approach, MCEM and Bayesian approaches using simulation, showing that they appear approximately equally efficient, with the approximate cross-validation method being computationally the most convenient. An example from equine epidemiology that motivated the work is used to demonstrate our approaches.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.217-222
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• 2009

In this paper, a new approach is proposed for the segmentation of Computed Tomography (CT) head images. The approach consists of two-stage segmentation with each stage contains two different segmentation techniques. The ultimate aim is to segment the CT head images into three classes which are abnormalities, cerebrospinal fluid (CSF) and brain matter. For the first stage segmentation, k-means and fuzzy c-means (FCM) segmentation are implemented in order to acquire the abnormalities. Whereas for the second stage segmentation, modified FCM with population-diameter independent (PDI) and expectation-maximization (EM) segmentation are adopted to obtain the CSF and brain matter. The experimental results have demonstrated that the proposed system is feasible and achieve satisfactory results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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• pp.400-405
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• 2001

Quadrature Amplitude Modulation(QAM) is well known a bandwidth efficient modulation scheme. However, its use for mobile communications has been limited due to noise and signal distortion. Recently, the QAM scheme is emerging as a new modulation scheme for a band-limited wireless system. In this paper, we propose an iterative decoding algorithm assuming QAM signal for a narrow-band mobile channel. The Algorithm is based on the EM(Expectation Maximization) Algorithm, and the performances of the proposed decoder are assessed using computer simulation. The simulation results show that the proposed decoder perform better compared to that of other schemes.