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Journal articles on the topic 'Matrix methods'

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Published: 4 June 2021
Last updated: 30 July 2024

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1

Davidson, Ernest R. "Super-matrix methods." Computer Physics Communications 53, no. 1-3 (May 1989): 49–60. http://dx.doi.org/10.1016/0010-4655(89)90147-1.

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2

Zito, Richard. "System Safety Matrix Methods." Journal of System Safety 52, no. 3 (January 1, 2017): 13–21. http://dx.doi.org/10.56094/jss.v52i3.119.

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The analysis of networks is a common feature in system safety analysis. These networks may range from electronic circuits to software flowcharts to maps of land, air, sea and communications traffic. Matrix methods are the natural tool for the analysis of these networks, and the object of this paper is to describe the basics of matrix methods in the context of three common problems encountered by systems safety engineers: the Bent Pin Problem, the Sneak Circuit Problem and the Analysis of Software Logic. Comparison of these analyses will reveal deep connections between these problems and suggest directions for future research.
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3

Hassan, M., F. Hammouda, and A. Asser. "MATRIX METHODS IN MAGNETOHYDRODYNAMICS." International Conference on Applied Mechanics and Mechanical Engineering 2, no. 2 (May 1, 1986): 213–20. http://dx.doi.org/10.21608/amme.1986.59015.

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4

Jain, Nitin A., Kushal D. Murthy, and Hamsapriye. "Matrix methods for finding." International Journal of Mathematical Education in Science and Technology 45, no. 5 (January 21, 2014): 754–62. http://dx.doi.org/10.1080/0020739x.2013.877607.

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5

Ridgely, Pat. "Matrix methods and circuits." American Journal of Physics 53, no. 11 (November 1985): 1038. http://dx.doi.org/10.1119/1.14028.

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6

Özarslan, H. S., and T. Ari. "Absolute matrix summability methods." Applied Mathematics Letters 24, no. 12 (December 2011): 2102–6. http://dx.doi.org/10.1016/j.aml.2011.06.006.

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7

Abraham, Leah C., J. Fred Dice, Patrick F. Finn, Nicholas T. Mesires, Kyongbum Lee, and David L. Kaplan. "Extracellular matrix remodeling—Methods to quantify cell–matrix interactions." Biomaterials 28, no. 2 (January 2007): 151–61. http://dx.doi.org/10.1016/j.biomaterials.2006.07.001.

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8

Dikshit, H. P., and J. A. Fridy. "Some absolutely effective product methods." International Journal of Mathematics and Mathematical Sciences 15, no. 4 (1992): 641–51. http://dx.doi.org/10.1155/s0161171292000851.

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It is proved that the product methodA(C,1), where(C,1)is the Cesàro arithmetic mean matrix, is totally effective under certain conditions concerning the matrixA. This general result is applied to study absolute Nörlund summability of Fourier series and other related series.
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9

Tian, Li-Ping, Lizhi Liu, and Fang-Xiang Wu. "Matrix Decomposition Methods in Bioinformatics." Current Bioinformatics 8, no. 2 (February 1, 2013): 259–66. http://dx.doi.org/10.2174/1574893611308020014.

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10

Zamarashkin, N. L., I. V. Oseledets, and E. E. Tyrtyshnikov. "New Applications of Matrix Methods." Computational Mathematics and Mathematical Physics 61, no. 5 (May 2021): 669–73. http://dx.doi.org/10.1134/s0965542521050183.

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11

Kosztyán, Zsolt Tibor, and Judit Kiss. "MATRIX-BASED PROJECT PLANNING METHODS." Problems of Management in the 21st Century 1, no. 1 (May 10, 2011): 67–85. http://dx.doi.org/10.33225/pmc/11.01.67.

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Network planning methods for project planning and scheduling have been applied for more than fifty years including CPM, PDM, PERT and GERT (Fondahl, 1961; Fulkerson, 1962; Kelley & Walker, 1959; PMI, 2006; Pritsker, 1966), which can be widely applied to project planning fromareas as diverse as construction and R&D. However, these network planning methods are not very appropriate in cases where IT, innovation or product development are involved. There are some shortcomings when using network planning methods for scheduling these kinds of projects, because these methods cannot handle the importance of the task realizations. They cannot solve the problem, when some tasks have to be left out from the project because of the constraints, or when the completion order of tasks can be different. In this paper new matrix-based project planning methods are introduced which illustrate how all possible solutions can be determined in two steps based on the Project Expert Matrix. Firstly those tasks are selected, which have to be or can be realized during the project. Afterwards the dependencies (the sequence of the chosen tasks) are determined taking the project constraints into account. The possible solutions can be ranked and the most probable solution can be chosen which can be realized within the given constraints. This method can be a useful tool for project managers as a part of an expert system. Key words: matrix-based project planning method, Project Expert Graph, Project Expert Matrix, Stochastic Network Planning Method.
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12

Jbilou, Khalide, Abderrahim Messaoudi, and Khalid Tabaa. "On some matrix extrapolation methods." Comptes Rendus Mathematique 341, no. 12 (December 2005): 781–86. http://dx.doi.org/10.1016/j.crma.2005.10.019.

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13

Özarslan, H. S., and H. N. Öğdük. "On absolute matrix summability methods." International Journal of Mathematics and Mathematical Sciences 2005, no. 16 (2005): 2517–22. http://dx.doi.org/10.1155/ijmms.2005.2517.

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14

Mugnolo, Delio. "Matrix methods for wave equations." Mathematische Zeitschrift 253, no. 4 (February 23, 2006): 667–80. http://dx.doi.org/10.1007/s00209-005-0925-3.

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15

Ishii, Akira, Yuichi Murayama, Yih-Lin Nien, Ichiro Yuki, P. Henry Adapon, Robert Kim, Reza Jahan, Gary Duckwiler, and Fernando Viñuela. "IMMEDIATE AND MIDTERM OUTCOMES OF PATIENTS WITH CEREBRAL ANEURYSMS TREATED WITH MATRIX1 AND MATRIX2 COILS." Neurosurgery 63, no. 6 (December 1, 2008): 1071–79. http://dx.doi.org/10.1227/01.neu.0000334047.30589.13.

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Abstract OBJECTIVE Recanalization after coil embolization of cerebral aneurysms remains a limitation of this progressively accepted modality. The Matrix detachable bioabsorbable coil (Boston Scientific Neurovascular, Natick, MA) was developed to overcome this limitation. We report a single-center experience using first- and second-generation Matrix coils. METHODS Immediate and midterm angiographic outcomes of 235 consecutive patients with 250 aneurysms treated with Matrix coils were reviewed retrospectively. The first 16 aneurysms included in the postmarket Acceleration of Connective Tissue Formation in Endovascular Aneurysm Repair (ACTIVE) study were treated exclusively with the Matrix coil, as per protocol. The next 234 aneurysms were treated in combination with bare platinum coils, stents, and the balloon-assisted technique. First-generation Matrix coils were used in 155 aneurysms (Matrix1 group) and second-generation Matrix coils were used in 79 aneurysms (Matrix2 group). Outcomes of the 3 groups were compared. RESULTS Immediate complete obliteration was achieved in 12.5% of the ACTIVE group aneurysms, 32.9% of the Matrix1 group, and 43.0% of the Matrix2 group. Overall, 87 (34.8%) aneurysms were completely occluded acutely. Procedure-related morbidity and mortality were 2.4 and 0%, respectively. Follow-up (median, 7.9 months) angiograms were obtained for 186 (74.4%) aneurysms. Complete obliteration of aneurysms was confirmed in 26.7% of the ACTIVE group, 53.4% of the Matrix1 group, and 64.2% of the Matrix2 group. Recanalization was observed in 33.3% of the ACTIVE group, 16.9% of the Matrix1 group, and 9.4% of the Matrix2 group. The overall recanalization rate was 16.1%. CONCLUSION Use of Matrix2 coils resulted in improved mechanical performance and anatomic outcome compared with Matrix1 coils. However, practitioners must be familiar with the mechanical characteristics of the Matrix coils, which are different from those of bare platinum coils.
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16

Liang, WanZhen, Roi Baer, Chandra Saravanan, Yihan Shao, Alexis T. Bell, and Martin Head-Gordon. "Fast methods for resumming matrix polynomials and Chebyshev matrix polynomials." Journal of Computational Physics 194, no. 2 (March 2004): 575–87. http://dx.doi.org/10.1016/j.jcp.2003.08.027.

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17

He, Qi-Ming. "Partial Orders and the Matrix R in Matrix Analytic Methods." SIAM Journal on Matrix Analysis and Applications 20, no. 4 (January 1999): 871–85. http://dx.doi.org/10.1137/s0895479897311214.

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18

Sun, Yuanxin. "Methods to Reduce Matrix Effect Corresponding to Different Methods." Theoretical and Natural Science 4, no. 1 (April 28, 2023): 365–69. http://dx.doi.org/10.54254/2753-8818/4/20220592.

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In this paper, LC-MS / MS is the main technology used to detect the toxins that cause diarrhea shellfish poisoning in shellfish toxins, including okadaic acid (OA) or its analogues, the dynophysistoxins (DTXds), spectenotoxin (PTX), yessotoxin and its derivatives (YTX) and azaspiracid (AZA). It is mainly found that when analyzing drugs in biological samples based on LC-MS / MS, Some extracts in the sample may affect the ionization efficiency of the target compound and thus affect the detection results, especially phospholipids. Based on the efforts made and innovative methods provided by other experimental methods that use this method to analyze other substances to solve or mitigate matrix effects, this paper proposes a potential solution to provide a reference way to solve matrix effects caused by phospholipids in DSP toxin detection, that is, three-step microelement can be used in the process.
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19

Ushenko, A. G. "Azimuthally invariant Mueller-matrix methods in the diagnosis of liver disease." Semiconductor Physics Quantum Electronics and Optoelectronics 19, no. 4 (December 5, 2016): 404–14. http://dx.doi.org/10.15407/spqeo19.04.404.

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20

Ongie, Greg, Daniel Pimentel-Alarcón, Laura Balzano, Rebecca Willett, and Robert D. Nowak. "Tensor Methods for Nonlinear Matrix Completion." SIAM Journal on Mathematics of Data Science 3, no. 1 (January 2021): 253–79. http://dx.doi.org/10.1137/20m1323448.

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21

Wituła, Roman, Damian Słota, Jarosław Matlak, Agata Chmielowska, and Michał Różański. "Matrix methods in evaluation of integrals." Journal of Applied Mathematics and Computational Mechanics 19, no. 1 (March 2020): 103–12. http://dx.doi.org/10.17512/jamcm.2020.1.09.

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22

KOHARA, Shiro. "Fabrication methods for aluminum matrix composites." Journal of Japan Institute of Light Metals 40, no. 9 (1990): 703–11. http://dx.doi.org/10.2464/jilm.40.703.

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23

Benahmed, Boubakeur, Bruno de Malafosse, and Adnan Yassine. "Matrix Transformations and Quasi-Newton Methods." International Journal of Mathematics and Mathematical Sciences 2007 (2007): 1–17. http://dx.doi.org/10.1155/2007/25704.

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We first recall some properties of infinite tridiagonal matrices considered as matrix transformations in sequence spaces of the formssξ,sξ∘,sξ(c), orlp(ξ). Then, we give some results on the finite section method for approximating a solution of an infinite linear system. Finally, using a quasi-Newton method, we construct a sequence that converges fast to a solution of an infinite linear system.
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24

Williams, F. W. "Teaching and Examining Sparse Matrix Methods." International Journal of Mechanical Engineering Education 23, no. 4 (October 1995): 336–42. http://dx.doi.org/10.1177/030641909502300406.

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A method is presented for concise teaching and examining of the principles and advantages of sparse matrix methods. The method uses only mental arithmetic and is illustrated using Gauss elimination for the solution of simultaneous equations. Indications are given of the ways in which the ideas can be extended to methods other than Gauss elimination and to types of sparse matrix method other than those considered in detail. Indications are also given of how the material can be taught so as to integrate with related matters, such as the evaluation of determinants and the way that the savings obtained by using the most sophisticated sparse matrix methods increase rapidly as the order of the matrix increases.
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25

Grieves, B., and D. Dunn. "Symmetric matrix methods for Schrodinger eigenvectors." Journal of Physics A: Mathematical and General 23, no. 23 (December 7, 1990): 5479–91. http://dx.doi.org/10.1088/0305-4470/23/23/021.

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26

CROZ, JEREMY J. DU, and NICHOLAS J. HIGHAM. "Stability of Methods for Matrix Inversion." IMA Journal of Numerical Analysis 12, no. 1 (1992): 1–19. http://dx.doi.org/10.1093/imanum/12.1.1.

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27

Constantine, Paul G., David F. Gleich, and Gianluca Iaccarino. "Spectral Methods for Parameterized Matrix Equations." SIAM Journal on Matrix Analysis and Applications 31, no. 5 (January 2010): 2681–99. http://dx.doi.org/10.1137/090755965.

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28

Jódar, L., J. L. Morera, and E. Navarro. "On convergent linear multistep matrix methods." International Journal of Computer Mathematics 40, no. 3-4 (January 1991): 211–19. http://dx.doi.org/10.1080/00207169108804014.

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29

Killingbeck, J. P., and G. Jolicard. "Perturbation methods for the matrix eigenproblem." Journal of Physics A: Mathematical and General 25, no. 23 (December 7, 1992): 6455–59. http://dx.doi.org/10.1088/0305-4470/25/23/037.

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30

Simoncini, V. "Computational Methods for Linear Matrix Equations." SIAM Review 58, no. 3 (January 2016): 377–441. http://dx.doi.org/10.1137/130912839.

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31

Bolten, Matthias, Thomas K. Huckle, and Christos D. Kravvaritis. "Sparse matrix approximations for multigrid methods." Linear Algebra and its Applications 502 (August 2016): 58–76. http://dx.doi.org/10.1016/j.laa.2015.11.008.

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32

Waterman, P. C. "T-matrix methods in acoustic scattering." Journal of the Acoustical Society of America 125, no. 1 (January 2009): 42–51. http://dx.doi.org/10.1121/1.3035839.

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33

Faragó, I., and P. Tarvainen. "Qualitative analysis of matrix splitting methods." Computers & Mathematics with Applications 42, no. 8-9 (October 2001): 1055–67. http://dx.doi.org/10.1016/s0898-1221(01)00221-8.

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34

Dymnikov, Alexander D. "Matrix methods in periodic focusing systems." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 427, no. 1-2 (May 1999): 6–11. http://dx.doi.org/10.1016/s0168-9002(98)01502-2.

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35

Mishchenko, M. I., and P. A. Martin. "Peter Waterman and T-matrix methods." Journal of Quantitative Spectroscopy and Radiative Transfer 123 (July 2013): 2–7. http://dx.doi.org/10.1016/j.jqsrt.2012.10.025.

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36

Engström, Alexander, and Florian Kohl. "Transfer-matrix methods meet Ehrhart theory." Advances in Mathematics 330 (May 2018): 1–37. http://dx.doi.org/10.1016/j.aim.2018.03.004.

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37

Falaleev, L. P. "On matrix summation methods inL p." Mathematical Notes 54, no. 5 (November 1993): 1154–58. http://dx.doi.org/10.1007/bf01208396.

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38

Alvarado, Fernando L. "Matrix enlarging methods and their application." BIT Numerical Mathematics 37, no. 3 (September 1997): 473–505. http://dx.doi.org/10.1007/bf02510237.

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39

Özgen, H. Nedret. "On two absolute matrix summability methods." Bollettino dell'Unione Matematica Italiana 9, no. 3 (February 3, 2016): 391–97. http://dx.doi.org/10.1007/s40574-016-0053-5.

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40

Kyrillidis, Anastasios, and Volkan Cevher. "Matrix Recipes for Hard Thresholding Methods." Journal of Mathematical Imaging and Vision 48, no. 2 (April 6, 2013): 235–65. http://dx.doi.org/10.1007/s10851-013-0434-7.

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41

Duff, Iain, and Bora Uçar. "Direct methods for sparse matrix solution." Scholarpedia 8, no. 10 (2013): 9700. http://dx.doi.org/10.4249/scholarpedia.9700.

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42

Stojčev, M. K., I. Ž Milovanović, and Ž Č Radonjić. "Some shifting methods for matrix multiplication." IEE Proceedings E Computers and Digital Techniques 132, no. 1 (1985): 33. http://dx.doi.org/10.1049/ip-e.1985.0004.

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43

Gill, Andrew W., G. E. Sneddon, and R. J. Hosking. "Matrix methods in barotropic stability analysis." Geophysical & Astrophysical Fluid Dynamics 72, no. 1-4 (November 1993): 57–92. http://dx.doi.org/10.1080/03091929308203607.

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44

Pietrzak, Katarzyna. "Metal Matrix Composites - methods of Joining." Advanced Composites Letters 4, no. 5 (September 1995): 096369359500400. http://dx.doi.org/10.1177/096369359500400505.

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45

Elser, Veit. "Matrix product constraints by projection methods." Journal of Global Optimization 68, no. 2 (September 19, 2016): 329–55. http://dx.doi.org/10.1007/s10898-016-0466-9.

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46

Mapstone, Mark, Amrita K. Cheema, Xiaogang Zhong, Massimo S. Fiandaca, and Howard J. Federoff. "Biomarker validation: Methods and matrix matter." Alzheimer's & Dementia 13, no. 5 (December 21, 2016): 608–9. http://dx.doi.org/10.1016/j.jalz.2016.11.004.

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47

Jelfimova, L. D. "New cellular methods for matrix multiplication." Cybernetics and Systems Analysis 49, no. 1 (January 2013): 15–25. http://dx.doi.org/10.1007/s10559-013-9480-9.

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48

Ammar, Gregory, and Clyde Martin. "The geometry of matrix eigenvalue methods." Acta Applicandae Mathematicae 5, no. 3 (March 1986): 239–78. http://dx.doi.org/10.1007/bf00047344.

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49

Su, Youfeng, and Guoliang Chen. "Iterative methods for solving linear matrix equation and linear matrix system." International Journal of Computer Mathematics 87, no. 4 (March 2010): 763–74. http://dx.doi.org/10.1080/00207160802195977.

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50

Yu, Bo, Ning Dong, Qiong Tang, and Feng-Hua Wen. "On iterative methods for the quadratic matrix equation with M-matrix." Applied Mathematics and Computation 218, no. 7 (December 2011): 3303–10. http://dx.doi.org/10.1016/j.amc.2011.08.070.

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