• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4C
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• pp.336-341
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• 2008

In this paper, beamforming algorithm is proposed which can obtain diversity gain in beamforming system that deploy antenna elements with half-wavelength. The proposed algorithm provides beam-pattern using eigen-vectors that span received signal subspace. The criterion to decide optimal rank of eigen-space used for beamforming is also proposed. A beamforming system applied the proposed algorithm shows better performance with diversity gain as getting larger angle spread. This paper provides a description of proposed algorithm with analysis of the performance using various computer simulations.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3E
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• pp.140-145
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• 2002

This paper introduces the downlink Eigen-beamformer with Space-Time Block Code (STBC)[1,2] employed on the MISO (Multiple Input Multiple Output) systems. The proposed scheme is acquired both transmit diversity gain from STBC and beamforming gain from Eigen-beamformer. In general, it is well described that the diversity gain be maximized when channel parameters associated to fingers are mutually independent. Major role of utilizing Eigen-beamformer is to enforce channel parameters being uncorrelated. According to this, the proposed STBC combined with Eigen-beamformer on the downlink significantly improves its performance under the spatially correlated channel. Simulation results are accomplished under three distinct channels conditioned with varying the degree of their correlations. The result indicates that our proposed scheme is good performance in spatially correlated channel.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1932-1935
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• 2002

This paper introduces the downlink Eigen-beamformer with Space-Time Block Code (STBC) 〔1,2〕employed on the MISO (Multiple Input Multiple Output) systems. The proposed scheme is acquired both transmit diversity gain from STBC and beamforming gain from Eigen-beamformer. In general, it is well described that the diversity gain be maximized when channel parameters associated to fingers are mutually independent. Major role f utilizing Eigen-beamformer is to enforce channel parameters being uncorrelated. According to this, the proposed STBC combined with Eigen-beamformer on the downlink significantly improves its performance under the spatially correlated channel. Simulation results are accomplished under three distinct channel conditioned with varying the degree of their correlations. The result indicates hat our proposed scheme is good performance in spatially correlated channel.

• Communications of the Korean Mathematical Society
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• v.29 no.1
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• pp.173-185
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• 2014

In the present paper, we consider an anomalous diffusion problem in two dimensional space involving Caputo time and Riesz-Feller fractional derivatives and then solve it by using a series involving bilateral eigen-functions. Also, we obtain a numerical approximation formula of this problem and discuss some of its particular cases.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.18-25
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• 2011

In a manufacturing process of metal coins, surface defects of coins are manually detected. This paper describes an new method for detecting surface defects of metal coins on a moving conveyor belt using image processing. This method consists of multiple procedures: segmentation of a coin from the background, alignment of the coin to the model, projection of the aligned coin to the best eigen image space, and detection of defects by comparison of the projection error with an adaptive threshold. In these procedures, the alignement and the projection are newly developed in this paper for the detection of coin surface defects. For alignment, we use the histogram of the segmented coin, which converts two-dimensional image alignment to one-dimensional alignment. The projection reduces the intensity variation of the coin image caused by illumination and coin rotation change. For projection, we build multiple eigen image spaces and choose the best eigen space using estimated coin direction. Since each eigen space consists of a small number of eigen image vectors, we can implement the projection in real- time.

• Journal of Communications and Networks
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• v.8 no.3
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• pp.275-285
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• 2006

Suitable for multi-input multi-output (MIMO) communications, the joint beamforming space-time block coding (JBSTBC) scheme is proposed for high-speed downlink transmission. The major functionality of the scheme entails space-time block encoder and joint transmit and receive eigen-beamformer (EBF) incorporating with block-ordered layered decoder (BOLD), and its operating principle is described in this paper. Within these functionalities, the joint EBFs will be utilized for decorrelating fading channels to cause an enhancement in the spatial diversity gain. Furthermore, to fortify the capability of layered successive interference cancellation (LSIC) in block-ordered layered decoding process, this paper will develop a simple ad-hoc transmit power discrimination scheme (TPDS) based on a particular power discrimination function (PDF). To confirm the superior behavior of the proposed JBSTBC scheme employing ad-hoc TPDS, computer simulations will be conducted under various channel conditions with the provision of detailed mathematical derivations for clarifying its functionality.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.705-708
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• 2010

An eigen color co-occurrence approach is proposed that exploits the correlation between color channels to identify the degree of image similarity. This method is based on traditional co-occurrence matrix method and histogram equalization. On the purpose of feature extraction, eigen color co-occurrence matrices are computed for extracting the statistical relationships embedded in color images by applying Principal Component Analysis (PCA) on a set of color co-occurrence matrices, which are computed on the histogram equalized images. That eigen space is created with a set of orthogonal axes to gain the essential structures of color co-occurrence matrices, which is used to identify the degree of similarity to classify an input image to be tested for various purposes. In this paper RGB, Gaussian color space are compared with grayscale image in terms of PCA eigen features embedded in histogram equalized co-occurrence features. The experimental results are presented.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.59-66
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• 2016

This paper presents an empirical evaluation on dimensionality reduction strategies by which dissimilarity-based classifications (DBC) can be implemented efficiently. In DBC, classification is not based on feature measurements of individual objects (a set of attributes), but rather on a suitable dissimilarity measure among the individual objects (pair-wise object comparisons). One problem of DBC is the high dimensionality of the dissimilarity space when a lots of objects are treated. To address this issue, two kinds of solutions have been proposed in the literature: prototype selection (PS)-based methods and dimension reduction (DR)-based methods. In this paper, instead of utilizing the PS-based or DR-based methods, a way of performing DBC in Eigen spaces (ES) is considered and empirically compared. In ES-based DBC, classifications are performed as follows: first, a set of principal eigenvectors is extracted from the training data set using a principal component analysis; second, an Eigen space is expanded using a subset of the extracted and selected Eigen vectors; third, after measuring distances among the projected objects in the Eigen space using $l_p$-norms as the dissimilarity, classification is performed. The experimental results, which are obtained using the nearest neighbor rule with artificial and real-life benchmark data sets, demonstrate that when the dimensionality of the Eigen spaces has been selected appropriately, compared to the PS-based and DR-based methods, the performance of the ES-based DBC can be improved in terms of the classification accuracy.

• MALSORI
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• no.52
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• pp.145-160
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• 2004

In this paper, a new noise compensation method based on the eigenvoice framework in feature space is proposed to reduce the mismatch between training and testing environments. The difference between clean and noisy environments is represented by the linear combination of K eigenvectors that represent the variation among environments. In the proposed method, the performance improvement of speech recognition systems is largely affected by how to construct the noisy models and the bias vector set. In this paper, two methods, the one based on MAP adaptation method and the other using stereo DB, are proposed to construct the noisy models. In experiments using Aurora 2 DB, we obtained 44.86% relative improvement with eigen-environment method in comparison with baseline system. Especially, in clean condition training mode, our proposed method yielded 66.74% relative improvement, which is better performance than several methods previously proposed in Aurora project.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.195-201
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• 1996

This paper is mainly forcused on the application of modal analysis In analyze the geometrically non-linear buckling behaviors of large span spatial structures, and the evaluation of each eigen mode affected post-buckling behaviors and buckling loads. Modal analysis is applied . to derivation of the system matrices transforming actual displacement space into generalized coordinates space represented by coefficients multiplied in the linear combination of eigen modes which are independent and orthogonal each other. By using modal analysis method, it will be expected to save the calculating time by computer extremely. For example, we can obtain the satisfactorily good results by using about 7% of total eigen modes only in case of single layer latticed dome. And we can decrease the possibility of divergence on the bifurcation point in the calculation of post-buckling path. Arc-length method and Newton-Raphson iteration method are used to calculate the nonlinear equilibrium path.