• Title/Summary/Keyword: problem matrix

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Inverse Eigenvalue Problems with Partial Eigen Data for Acyclic Matrices whose Graph is a Broom

  • Sharma, Debashish;Sen, Mausumi
    • Kyungpook Mathematical Journal
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    • v.57 no.2
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    • pp.211-222
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    • 2017
  • In this paper, we consider three inverse eigenvalue problems for a special type of acyclic matrices. The acyclic matrices considered in this paper are described by a graph called a broom on n + m vertices, which is obtained by joining m pendant edges to one of the terminal vertices of a path on n vertices. The problems require the reconstruction of such a matrix from given partial eigen data. The eigen data for the first problem consists of the largest eigenvalue of each of the leading principal submatrices of the required matrix, while for the second problem it consists of an eigenvalue of each of its trailing principal submatrices. The third problem has an eigenvalue and a corresponding eigenvector of the required matrix as the eigen data. The method of solution involves the use of recurrence relations among the leading/trailing principal minors of ${\lambda}I-A$, where A is the required matrix. We derive the necessary and sufficient conditions for the solutions of these problems. The constructive nature of the proofs also provides the algorithms for computing the required entries of the matrix. We also provide some numerical examples to show the applicability of our results.

A response matrix method for the refined Analytic Function Expansion Nodal (AFEN) method in the two-dimensional hexagonal geometry and its numerical performance

  • Noh, Jae Man
    • Nuclear Engineering and Technology
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    • v.52 no.11
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    • pp.2422-2430
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    • 2020
  • In order to improve calculational efficiency of the CAPP code in the analysis of the hexagonal reactor core, we have tried to implement a refined AFEN method with transverse gradient basis functions and interface flux moments in the hexagonal geometry. The numerical scheme for the refined AFEN method adopted here is the response matrix method that uses the interface partial currents as nodal unknowns instead of the interface fluxes used in the original AFEN method. Since the response matrix method is single-node based, it has good properties such as good calculational efficiency and parallel computing affinity. Because a refined AFEN method equivalent nonlinear FDM response matrix method tried first could not provide a numerically stable solution, a direct formulation of the refined AFEN response matrix were developed. To show the numerical performance of this response matrix method against the original AFEN method, the numerical error analyses were performed for several benchmark problems including the VVER-440 LWR benchmark problem and the MHTGR-350 HTGR benchmark problem. The results showed a more than three times speedup in computing time for the LWR and HTGR benchmark problems due to good convergence and excellent calculational efficiency of the refined AFEN response matrix method.

Fast Calculation of Capacitance Matrix for Strip-Line Crossings and Other Interconnects (교차되는 스트립 라인구조에서의 빠른 커패시턴스 계산기법)

  • Srinivasan Jegannathan;Lee Dong-Jun;Shim Duk-Sun;Yang Cheol-Kwan;Kim Hyung-Kyu;Kim Hyeong-Seok
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.53 no.10
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    • pp.539-545
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    • 2004
  • In this paper, we consider the problem of capacitance matrix calculation for strip-line and other interconnects crossings. The problem is formulated in the spectral domain using the method of moments. Sinc-functions are employed as basis functions. Conventionally, such a formulation leads to a large, non-sparse system of linear equations in which the calculation of each of the coefficient requires the evaluation of a Fourier-Bessel integral. Such calculations are computationally very intensive. In the method proposed here, we provide simplified expressions for the coefficients in the moment method matrix. Using these simplified expressions, the coefficients can be calculated very efficiently. This leads to a fast evaluation of the capacitance matrix of the structure. Computer simulations are provided illustrating the validity of the method proposed.

Thermal Stresses in a Laminated Fiber-Reinforced Composite Containing an Interlaminar Crack Under a Uniform Heat Flow (층간균열이 존재하는 균일 열유동하의 섬유강화 적층복합재료의 열응력해석)

  • 최형집;오준성;이강용
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.4
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    • pp.887-902
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    • 1994
  • Within the framework of anisotropic thermoelasticity, the problem of an interlaminar crack in a laminated fiber-reinforced composite subjected to a uniform heat flow is investigated. Under a state of generalized plane deformation, dissimilar anisotropic half-spaces with different fiber orientations are considered to be bound together by a matrix interlayer containing the crack. The interlayer models the matrix-rich interlaminar region of the fibrous composite laminate. Based on the flexibility/stiffness matrix approach, formulation of the current crack problem results in having to solve two sets of singular integral equations for temperature and thermal stress analyses. Numerical results are obtained, illustrating the parametric effects of laminate stacking sequence, relative crack size, crack location, crack surface partial insulation, and fiber volume fraction on the values of mixed mode thermal stress intensity factors.

THE (R,S)-SYMMETRIC SOLUTIONS TO THE LEAST-SQUARES PROBLEM OF MATRIX EQUATION AXB = C

  • Liang, Mao-Lin;Dai, Li-Fang;Wang, San-Fu
    • Journal of applied mathematics & informatics
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    • v.27 no.5_6
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    • pp.1061-1071
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    • 2009
  • For real generalized reflexive matrices R, S, i.e., $R^T$ = R, $R^2$ = I, $S^T$ = S, $S^2$ = I, we say that real matrix X is (R,S)-symmetric, if RXS = X. In this paper, an iterative algorithm is proposed to solve the least-squares problem of matrix equation AXB = C with (R,S)-symmetric X. Furthermore, the optimal approximation solution to given matrix $X_0$ is also derived by this iterative algorithm. Finally, given numerical example and its convergent curve show that this method is feasible and efficient.

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A𝛼-SPECTRAL EXTREMA OF GRAPHS WITH GIVEN SIZE AND MATCHING NUMBER

  • Xingyu Lei;Shuchao Li;Jianfeng Wang
    • Bulletin of the Korean Mathematical Society
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    • v.60 no.4
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    • pp.873-893
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    • 2023
  • In 2017, Nikiforov proposed the A𝛼-matrix of a graph G. This novel matrix is defined as A𝛼(G) = 𝛼D(G) + (1 - 𝛼)A(G), 𝛼 ∈ [0, 1], where D(G) and A(G) are the degree diagonal matrix and adjacency matrix of G, respectively. Recently, Zhai, Xue and Liu [39] considered the Brualdi-Hoffman-type problem for Q-spectra of graphs with given matching number. As a continuance of it, in this contribution we consider the Brualdi-Hoffman-type problem for A𝛼-spectra of graphs with given matching number. We identify the graphs with given size and matching number having the largest A𝛼-spectral radius for ${\alpha}{\in}[{\frac{1}{2}},1)$.

$H_ {\infty}$ PID Controller Design for an Attraction Type Magnetic Levitation System (흡인식 자기부상시스템의 $H_ {\infty}$ PID 제어기 설계)

  • Kim, Seog-Joo;Kim, Chun-Kyung;Kwon, Soon-Man
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.9
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    • pp.1624-1627
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    • 2008
  • This paper deals with a linear matrix inequality (LMI) approach to the design of a PID controller for an attraction type magnetic levitation system. First, we convert the $H_ {\infty}$ PID controller problem into a static output feedback problem. We then solve the static output problem by using the recently developed penalty function method. Numerical experiments show the effectiveness of the proposed algorithm.

PERMANENTS OF DOUBLY STOCHASTIC FERRERS MATRICES

  • Hwang, Suk-Geun;Pyo, Sung-Soo
    • Journal of the Korean Mathematical Society
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    • v.36 no.5
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    • pp.1009-1020
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    • 1999
  • The minimum permanent and the set of minimizing matrices over the face of the polytope n of all doubly stochastic matrices of order n determined by any staircase matrix was determined in [4] in terms of some parameter called frame. A staircase matrix can be described very simply as a Ferrers matrix by its row sum vector. In this paper, some simple exposition of the permanent minimization problem over the faces determined by Ferrers matrices of the polytope of n are presented in terms of row sum vectors along with simple proofs.

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Improved Face Recognition based on 2D-LDA using Weighted Covariance Scatter (가중치가 적용된 공분산을 이용한 2D-LDA 기반의 얼굴인식)

  • Lee, Seokjin;Oh, Chimin;Lee, Chilwoo
    • Journal of Korea Multimedia Society
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    • v.17 no.12
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    • pp.1446-1452
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    • 2014
  • Existing LDA uses the transform matrix that maximizes distance between classes. So we have to convert from an image to one-dimensional vector as training vector. However, in 2D-LDA, we can directly use two-dimensional image itself as training matrix, so that the classification performance can be enhanced about 20% comparing LDA, since the training matrix preserves the spatial information of two-dimensional image. However 2D-LDA uses same calculation schema for transformation matrix and therefore both LDA and 2D-LDA has the heteroscedastic problem which means that the class classification cannot obtain beneficial information of spatial distances of class clusters since LDA uses only data correlation-based covariance matrix of the training data without any reference to distances between classes. In this paper, we propose a new method to apply training matrix of 2D-LDA by using WPS-LDA idea that calculates the reciprocal of distance between classes and apply this weight to between class scatter matrix. The experimental result shows that the discriminating power of proposed 2D-LDA with weighted between class scatter has been improved up to 2% than original 2D-LDA. This method has good performance, especially when the distance between two classes is very close and the dimension of projection axis is low.

A Novel Compressed Sensing Technique for Traffic Matrix Estimation of Software Defined Cloud Networks

  • Qazi, Sameer;Atif, Syed Muhammad;Kadri, Muhammad Bilal
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.4678-4702
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    • 2018
  • Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.