• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.113-126
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• 2007

Let A and E be $m{\times}n$ matrices and W an $n{\times}m$ matrix, and let $A_{d,w}$ denote the W-weighted Drazin inverse of A. In this paper, a new representation of the W-weighted Drazin inverse of A is given. Some new properties for the W-weighted Drazin inverse $A_{d,w}\;and\;B_{d,w}$ are investigated, where B=A+E. In addition, the Banach-type perturbation theorem for the W-weighted Drazin inverse of A and B are established, and the perturbation bounds for ${\parallel}B_{d,w}{\parallel}\;and\;{\parallel}B_{d,w}-A_{d,w}{\parallel}/{\parallel}A_{d,w}{\parallel}$ are also presented. When A and B are square matrices and W is identity matrix, some known results in the literature related to the Drazin inverse and the group inverse are directly reduced by the results in this paper as special cases.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.84-85
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• 2019

MPEG-NNR (Compression of Neural Network for Multimedia Content Description and Analysis) aims to define a compressed and interoperable representation of trained neural networks. In this paper, we present a low-rank approximation to compress a CNN used for image compression, which is one of MPEG-NNR use cases. In the presented method, the low-rank approximation decomposes one 2D kernel matrix of weights into two 1D kernel matrix values in each convolution layer to reduce the data amount of weights. The evaluation results show that the model size of the original CNN is reduced to half as well as the inference runtime is reduced up to about 30% with negligible loss in PSNR.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2061-2074
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• 1998

In pattern recognition and image analysis upplications, a graph is a useful tool for complex obect representation and recognition. However it takes much time to pair proper nodes between the prototype graph and an input data graph. Futhermore it is difficult to decide whether the two graphs in a class are the same hecause real images are degradd in general by noise and other distortions. In this paper we propose a matching algorithm using a matrix. The matrix is suiable for simple and easily understood representation and enables the ordering and matching process to be convenient due to its predefined matrix manipulation. The nodes which constitute a gaph are ordered in the matrix by their geometrical positions and this makes it possible to save much comparison time for finding proper node pairs. for the classification, we defined a distance measure thatreflects the symbo's structural aspect that is the sum of the mode distance and the relation distance; the fornet is from the parameters describing the node shapes, the latter from the relations with othes node in the matrix. We also introduced a subdivision operation to compensate node merging which is mainly due t the prepreocessing error. The proposed method is applied to the recognition of musteal symbols and the result is given. The result shows that almost all, except heavily degraded symbols are recognized, and the recognition rate is approximately 95 percent.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.267-273
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• 2009

A representation for the Drazin inverse of an arbitrary square matrix in terms of the eigenprojection was established by Rothblum [SIAM J. Appl. Math., 31(1976) :646-648]. In this paper perturbation results based on the representation for the Darzin inverse $A^D\;=\;(A-X)^{-1}(I-X)$ are developed. Norm estimates of $\parallel(A+E)^D-A^D\parallel_2/\parallel A^D\parallel_2$ and $\parallel(A+E)^#-A^D\parallel_2/\parallel A^D\parallel_2$ are derived when IIEI12 is small.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.337-340
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• 2000

In this paper, we put forth a procedure that target low power logic synthesis based on XOR representation of Boolean functions, and the results of synthesis procedure are a multi-level XOR form with minimum switching activity. Specialty, this paper show a method to extract the common cubes or kernels by Boolean matrix and rectangle covering, and to estimate the power consumption in terms of the extracted common sub-functions.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.182-188
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• 2004

This paper presents a design method of delay-dependent control for T-S fuzzy systems with time delays. Based on parallel distributed compensation (PDC) and a descriptor model transformation of the system, a delay-dependent control is utilized. An appropriate Lyapunov-Krasovskii functional is chosen for delay-dependent stability analysis. A sufficient condition for delay-dependent control is represented in terms of linear matrix inequalities (LMIs).

• Communications of the Korean Mathematical Society
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• v.32 no.4
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• pp.999-1008
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• 2017

By mainly using certain properties arising from the semisimple Lie group SO(2, 1), we aim to show how a family of some interesting formulas for bilateral series and integrals involving Whittaker, Bessel functions, and their product can be obtained.

• Honam Mathematical Journal
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• v.42 no.2
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• pp.269-291
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• 2020

In this paper, we get acquainted to a new generalization of the modified Hermite matrix polynomials. An explicit representation and expansion of the Matrix exponential in a series of these matrix polynomials is obtained. Some important properties of Modified Hermite Matrix polynomials such as generating functions, recurrence relations which allow us a mathematical operations. Also we drive expansion formulae and some operational representations.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.1-5
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• 2011

In order to analyze the impedance properties of high integrated impedance network with multiple terminals, this paper introduces the concept of impedance relation matrix(IRM). The linear relation between the terminal voltages and currents is represented in the form of IRM and this matrix can be utilized to calculate the impedance between any two terminals. Furthermore, IRM representation for 2-port impedance network can be also defined. The whole impedance network is divided into the several 2-port sub-networks and each sub-network is analyzed in a form of the IRM representation. An illustrated example is given to show that the proposed method is simple and effective to analyze the impedance of a sensor array which has a very large number of impedance elements.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.55-62
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• 2017

Non-negative matrix factorization (NMF) is one of the typical parts-based representation in which images are expressed as a linear combination of basis vectors that show the lcoal features or objects in the images. In this paper, we represent face images using various NMF methods and recognize their face identities based on extracted features using a learning vector quantization. We analyzed the various NMF methods by comparing extracted basis vectors. Also we confirmed the availability of NMF to the face recognition by verification of recognition rate of the various NMF methods.