• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4A
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• pp.399-406
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• 2011

Adaptive beamformers, which utilize a priori information on the arrival angle of the desired signal. suppress interferences while maximizing their gains in the desired signal direction. However, if there exist errors in the direction information, they can suffer from severe performance degradation since the desired signal is treated as an interference. A robust adaptive beamforming method is presented which exploits the signal-blocking structure of the Duvall beamformer. The proposed method finds an interference signal space directly from correlations of received signals and then obtains a weight vector such that it is orthogonal to the space. Applying the weight vector to two sub arrays which consist of one less sensors than the original uniform lineal array (ULA), the beamformer efficiently estimates the arrival angle of the desired signal. Its computational complexity is lower than existing methods, which require matrix inversion or eigendecomposition.

• Structural Engineering and Mechanics
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• v.38 no.3
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• pp.261-281
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• 2011

A new method of formulation of a class of elements that are immune to mesh distortion effects is proposed here. The simple three-noded bar element with an offset of the internal node from the element center is employed here to demonstrate the method and the principles on which it is founded upon. Using the function space approach, the modified formulation is shown here to be superior to the conventional isoparametric version of the element since it satisfies the completeness requirement as the metric formulation, and yet it is in agreement with the best-fit paradigm in both the metric and the parametric domains. Furthermore, the element error is limited to only those that are permissible by the classical projection theorem of strains and stresses. Unlike its conventional counterpart, the modified element is thus not prone to any errors from mesh distortion. The element formulation is symmetric and thus satisfies the requirement of the conservative nature of problems associated with all self-adjoint differential operators. The present paper indicates that a proper mapping set for distortion immune elements constitutes geometric and displacement interpolations through parametric and metric shape functions respectively, with the metric components in the displacement/strain replaced by the equivalent geometric interpolation in parametric co-ordinates.

• Structural Engineering and Mechanics
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• v.69 no.6
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• pp.615-626
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• 2019

The 3-noded metric Timoshenko beam element with an offset of the internal node from the element centre is used here to demonstrate the best-fit paradigm using function space formulation under locking and mesh distortion. The best-fit paradigm follows from the projection theorem describing finite element analysis which shows that the stresses computed by the displacement finite element procedure are the best approximation of the true stresses at an element level as well as global level. In this paper, closed form best-fit solutions are arrived for the 3-noded Timoshenko beam element through function space formulation by combining field consistency requirements and distortion effects for the element modelled in metric Cartesian coordinates. It is demonstrated through projection theorems how lock-free best-fit solutions are arrived even under mesh distortion by using a consistent definition for the shear strain field. It is shown how the field consistency enforced finite element solution differ from the best-fit solution by an extraneous response resulting from an additional spurious force vector. However, it can be observed that when the extraneous forces vanish fortuitously, the field consistent solution coincides with the best-fit strain solution.

• Atmosphere
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• v.19 no.2
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• pp.107-125
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• 2009

Statistical downscaled surface temperature datasets by employing the cyclostationary empirical orthogonal function (CSEOF) analysis and multiple linear regression method are examined. For evaluating the efficiency of this statistical downscaling method, monthly surface temperature of the ECMWF has been downscaled into monthly temperature having a fine spatial scale of ~20km over the Korean peninsula for the 1973-2000 period. Monthly surface temperature of the ECHOG has also been downscaled into the same spatial scale data for the same period. Comparisons of temperatures between two datasets over the Korean peninsula show that annual mean temperature of the ECMWF is about $2^{\circ}C$ higher than that of the ECHOG. After applying to the statistical downscaling method, the difference of two annual mean temperatures reduces less than $1^{\circ}C$ and their spatial patterns become even close to each other. Future downscaled data shows that annual temperatures in the A1B scenario will increase by $3.5^{\circ}C$ by the late 21st century. The downscaled data are influenced by the ECHOG as well as observation data which includes effects of complicated topography and the heat island.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.717-725
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• 2000

Within the last several years, there has been a large number of algorithms developed for face recognition. The majority of these algorithms have been view- and projection-based algorithms. Our definition of projection is not restricted to projecting the image onto an orthogonal basis the definition is expansive and includes a general class of linear transformation of the image pixel values. The class includes correlation, principal component analysis, clustering, gray scale projection, and matching pursuit filters. In this paper, we perform a detailed analysis of this class of algorithms by evaluating them on the FERET database of facial images. In our experiments, a projection-based algorithms consists of three steps. The first step is done off-line and determines the new basis for the images. The bases is either set by the algorithm designer or is learned from a training set. The last two steps are on-line and perform the recognition. The second step projects an image onto the new basis and the third step recognizes a face in an with a nearest neighbor classifier. The classification is performed in the projection space. Most evaluation methods report algorithm performance on a single gallery. This does not fully capture algorithm performance. In our study, we construct set of independent galleries. This allows us to see how individual algorithm performance varies over different galleries. In addition, we report on the relative performance of the algorithms over the different galleries.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.380-388
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• 2000

In computing the optical flow, Horn and Schunck's method which is a representative algorithm is based on differentiation. Therefore it is difficult to estimate the velocity for a large displacement by this algorithm. In this paper, we propose a method for estimating nonuniform motion from sequential images which is based on integral brightness constancy constraints. The equations which transform a source image to a target image are expressed as a function of the displacement field. If marginal effects can be neglected, the form of the transformation integral transform or orthogonal expansion can be determined from the expansion coefficients of the two images. The apparent displacement field is then computed iteratively by a projection method which utilities the functional derivatives of the linearized moment equations. We demonstrate that the performance of the orthogonal function transform on the data set of large motion.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2566-2569
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• 2003

An alternative optimal control law formulation is introduced and compared with two different control law, a conventional linear quadratic regulator and the control law based on game theory. This formulation eliminates the undesired modes of the system by the projection of a controller onto the subspace orthogonal to that of the bad modes. In conventional LQR control law, the control performance can be improved only by using proper weighting matrices in performance index, normally, with high cost. The control law formulation by game theory may provide various ways to obtain the desired performance. The control law modified by the elimination of bad modes provides efficient ways to get rid of an undesired performance since it eliminates the exact modes which cause the bad control performance.

• Communications of the Korean Mathematical Society
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• v.18 no.3
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• pp.469-479
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• 2003

Let B be the open unit ball in $C^{n}$ and ${\mu}_{q}$(q > -1) the Lebesgue measure such that ${\mu}_{q}$(B) ＝ 1. Let ${L_{a,q}}^2$ be the subspace of ${L^2(B,D{\mu}_q)$ consisting of analytic functions, and let $\overline{{L_{a,q}}^2}$ be the subspace of ${L^2(B,D{\mu}_q)$) consisting of conjugate analytic functions. Let $\bar{P}$ be the orthogonal projection from ${L^2(B,D{\mu}_q)$ into $\overline{{L_{a,q}}^2}$. The little Hankel operator ${h_{\varphi}}^{q}\;:\;{L_{a,q}}^2\;{\rightarrow}\;{\overline}{{L_{a,q}}^2}$ is defined by ${h_{\varphi}}^{q}(\cdot)\;=\;{\bar{P}}({\varphi}{\cdot})$. In this paper, we will find the necessary and sufficient condition that the little Hankel operator ${h_{\varphi}}^{q}$ is bounded(or compact).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.247-250
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• 2001

In this paper, we propose an growing and pruning algorithm to design the adaptive structure of modular wavelet neural network(MWNN) with F-projection and geometric growing criterion. Geometric growing criterion consists of estimated error criterion considering local error and angle criterion which attempts to assign wavelet function that is nearly orthogonal to all other existing wavelet functions. These criteria provide a methodology that a network designer can constructs wavelet neural network according to one's intention. The proposed growing algorithm grows the module and the size of modules. Also, the pruning algorithm eliminates unnecessary node of module or module from constructed MWNN to overcome the problem due to localized characteristic of wavelet neural network which is used to modules of MWNN. We apply the proposed constructing algorithm of the adaptive structure of MWNN to approximation problems of 1-D function and 2-D function, and evaluate the effectiveness of the proposed algorithm.

• Journal of the Korean Magnetic Resonance Society
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• v.21 no.4
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• pp.119-125
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• 2017

The plucking season of green tea leaves is one of the important parameters that decide their metabolic diversity, quality, and prices. The effects of plucking sghlwleasons on green tea metabolites were investigated through metabolite profiling by $^1H$ NMR spectroscopy. The orthogonal projection on latent structure-discriminant analysis (OPLS-DA) showed clear discriminations of green teas by three different grades depending on plucking seasons: Ujeon, Sejak, and Jungjak. These results suggested that the nine peak groups could be used for diagnostics for identification of high quality Ujeon grade of green tea.