Auteurs : Boito, Paola (Auteur de la Conférence)
CIRM (Editeur )
Résumé :
Structure is a fundamental concept in linear algebra: matrices arising from applications often inherit a special form from the original problem, and this special form can be analysed and exploited to design efficient algorithms. In this short course we will present some examples of matrix structure and related applications. Here we are interested in data-sparse structure, that is, structure that allows us to represent an n × n matrix using only O(n) parameters. One notable example is provided by quasi separable matrices, a class of (generally dense) rank-structured matrices where off-diagonal blocks have low rank.
We will give an overview of the properties of these structured classes and present a few examples of how algorithms that perform basic tasks – e.g., solving linear systems, computing eigenvalues, approximating matrix functions – can be tailored to specific structures.
Keywords : structured matrices; eigenvalue computation; functions of matrices
Codes MSC :
65F15
- Eigenvalues, eigenvectors
65F60
- Matrix exponential and similar matrix functions (numerical linear algebra) - Numerical computation of matrix exponential and similar matrix functions
15B99
- Special matrices
Ressources complémentaires :
https://www.cirm-math.fr/RepOrga/2564/Slides/01_slidesBoito.pdf
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Informations sur la Rencontre
Nom de la rencontre : French Computer Algebra Days / JNCF - Journées nationales de calcul formel Organisateurs de la rencontre : Bardet, Magali ; Busé, Laurent ; Koseleff, Pierre-Vincent ; Vaccon, Tristan Dates : 01/03/2021 - 05/03/2021
Année de la rencontre : 2021
URL Congrès : https://conferences.cirm-math.fr/2564.html
DOI : 10.24350/CIRM.V.19718703
Citer cette vidéo:
Boito, Paola (2021). Topics in structured linear algebra - lecture 1. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19718703
URI : http://dx.doi.org/10.24350/CIRM.V.19718703
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Voir aussi
Bibliographie
- AURENTZ, Jared L., MACH, Thomas, ROBOL, Leonardo, et al. Core-chasing algorithms for the eigenvalue problem. Society for Industrial and Applied Mathematics, 2018. -
- BOITO, Paola, EIDELMAN, Yuli, et GEMIGNANI, Luca. Implicit QR for companion-like pencils. Mathematics of Computation, 2016, vol. 85, no 300, p. 1753-1774. - https://doi.org/10.1090/mcom/3020
- BOITO, Paola, EIDELMAN, Yuli, et GEMIGNANI, Luca. Efficient solution of parameter‐dependent quasiseparable systems and computation of meromorphic matrix functions. Numerical Linear Algebra with Applications, 2018, vol. 25, no 6, p. e2141. - https://doi.org/10.1002/nla.2141
- EIDELMAN, Yuli, GOHBERG, Israel, et HAIMOVICI, Iulian. Separable type representations of matrices and fast algorithms. Birkhäuser, Vol 1& 2 , 2014. - http://dx.doi.org/10.1007/978-3-0348-0606-0
- HIGHAM, Nicholas J. Functions of matrices: theory and computation. Society for Industrial and Applied Mathematics, 2008. - https://doi.org/10.1137/1.9780898717778
- VANDEBRIL, Raf, VAN BAREL, Marc, et MASTRONARDI, Nicola. Matrix computations and semiseparable matrices: linear systems. JHU Press, 2007. -