• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.34-42
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• 2012

Low density parity check (LDPC) code is widely used, since it shows superior performance close to Shannon limit and its decoding complexity is lower than turbo code. Recently, it is used as a channel code to decode Wyner-Ziv frames in distributed video coding (DVC) system. In this paper, we propose an efficient method to design the parity check matrix H of LDPC codes. In order to apply LDPC code to DVC system, the LDPC code should have rate compatibility. Thus, we also propose a method to merge check nodes of LDPC code to attain the rate compatibility. LDPC code is designed using ACE algorithm and check nodes are merged for a given code rate to maximize the error correction capability. The performance of the designed LDPC code is analyzed extensively by computer simulations.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.479-485
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• 2009

When a part of data is unobserved the marginal likelihood of parameters given the observed data often involves analytically intractable high dimensional integral and hence it is hard to find the maximum likelihood estimate of the parameters. Simulated maximum likelihood(SML) method which estimates the marginal likelihood via Monte Carlo importance sampling and optimize the estimated marginal likelihood has been used in many applications. A key issue in SML is to find a good proposal density from which Monte Carlo samples are generated. The optimal proposal density is the conditional density of the unobserved data given the parameters and the observed data, and attempts have been given to find a good approximation to the optimal proposal density. Algorithms which adaptively improve the proposal density have been widely used due to its simplicity and efficiency. In this paper, we describe a fully adaptive algorithm which has been used by some practitioners but has not been well recognized in statistical literature, and evaluate its estimation performance and robustness via a simulation study. The simulation study shows a great improvement in the order of magnitudes in the mean squared error, compared to non-adaptive or partially adaptive SML methods. Also, it is shown that the fully adaptive SML is robust in a sense that it is insensitive to the starting points in the optimization routine.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.128-137
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• 2002

In this paper, we propose the LPC+-file for efficient indexing of high-dimensional image data. With the proliferation of multimedia data, there Is an increasing need to support the indexing and retrieval of high-dimensional image data. Recently, the LPC-file (5) that based on vector approximation has been developed for indexing high-dimensional data. The LPC-file gives good performance especially when the dataset is uniformly distributed. However, compared with for the uniformly distributed dataset, its performance degrades when the dataset is clustered. We improve the performance of the LPC-file for the strongly clustered image dataset. The basic idea is to adaptively partition the data space to find subspaces with high-density clusters and to assign more bits to them than others to increase the discriminatory power of the approximation of vectors. The total number of bits used to represent vector approximations is rather less than that of the LPC-file since the partitioned cells in the LPC+-file share the bits. An empirical evaluation shows that the LPC+-file results in significant performance improvements for real image data sets which are strongly clustered.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.847-851
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• 2004

In the original mixture density network(MDN), which was introduced by Bishop and Nabney, the parameters of the conditional probability density function are represented by the output vector of a single multi-layer perceptron. Among the recent modification of the MDNs, there is the so-called modified mixture density network, in which each of the priors, conditional means, and covariances is represented via an independent multi-layer perceptron. In this paper, we consider a further simplification of the modified MDN, in which the conditional means are linear with respect to the input variable together with the development of the MATLAB program for the simplification. In this paper, we first briefly review the original mixture density network, then we also review the modified mixture density network in which independent multi-layer perceptrons play an important role in the learning for the parameters of the conditional probability, and finally present a further modification so that the conditional means are linear in the input. The applicability of the presented method is shown via an illustrative simulation example.

• Journal of the Optical Society of Korea
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• v.2 no.2
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• pp.58-63
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• 1998

Cross-talk effects in high-density volume holographic interconnections are investigated using perturbative iteration method of the integral form of Maxwell's wave equation. In this method, the paraxial approximation and negligence of backward scattering introduced in conventional coupled mode theory is not assumed. Interaction geometries consisting of non-coplanar light waves and multiple index gratings are studied. Arbitrary light polarization is considered. Systematic analysis of cross-talk effects due to multiple index gratings is performed in increasing level of diffraction orders corresponding to successive iterations. Some numerical examples are given for first and third order diffraction.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.664-666
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• 2004

본 논문에서는 영상의 누적분포함수(CDF: Cumulative Density Function)를 이용한 콘트라스트 향상 기법을 제안하였다 제안된 알고리즘은 처리된 영상에 영향물 주지 않으면서 최대 콘트라스트를 얻을 수 있었다. 하드웨어의 복잡성을 감소하기 위하여 누적분포함수의 샘플값을 이용한 선형화 방법을 이용하였다. 제안한 방식의 알고리즘 검증을 위하여 C를 이용하였으며, 처리 결과와 원 영상의 화질 평가를 위하여 시각적 검증과 히스토그램 편차를 도입하였다.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.55.1-55.1
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• 2016

We have developed a module for the dust continuum radiative transfer calculation as part of "Packages of Unified modeling for Radiative transfer, gas Energetics, and Chemistry (PUREC)". PUREC will be applied to interprete observations of protoplanetary disks. When a disk is under the hydrostatic equilibrium condition, the dust temperature and the vertical density structure should be calculated simultaneously. This module calculates the dust temperature by using the method of mean intensity (Lucy et al. 1999). In the very optically thick mid-palne, the Monte-carlo method is not efficient, thus, we apply "modified random walk" and "Partial Diffusion Approximation" to the module. The module has been verified by bechmark tests.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.341-345
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• 2010

It is known that the accuracy of DEM is related with terrain morphology, sampling density, and interpolation method. However, the theoretical reasons for these correlations have rarely been accounted for so far. This study aimed to verify a theoretical basis that DEM accuracy can be assessed based on approximation theory when we generate a DEM using lots of precise and accurate source data such as digital maps and LIDAR data.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1989.10a
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• pp.19-24
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• 1989

The electron energy distribution function in mercury discharge positive columns are calculated numerically from the Boltzmann eqation under a set of parameters, such as the electron temperature to. the atomic temperature Tw. the electron number density no. and the electric field E. Especially, using the approximation that collision cross sections only depend on the energy, the calculated electron energy distribution function was shown that it falls off rapidly in the high energy tail.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1217-1222
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• 2011

In this paper, we show that any circular density can be closely approximated by an exponential family of distributions. Therefore we propose an exponential family of distributions as a new family of circular distributions, which is absolutely suitable to model any shape of circular distributions. In this family of circular distributions, the trigonometric moments are found to be the uniformly minimum variance unbiased estimators (UMVUEs) of the parameters of distribution. Simulation result and goodness of fit test using an asymmetric real data set show usefulness of the novel circular distribution.