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001 978-3-319-57304-5
003 DE-He213
005 20210118133633.0
007 cr nn 008mamaa
008 170919s2017 gw | s |||| 0|eng d
020 _a9783319573045
_9978-3-319-57304-5
024 7 _a10.1007/978-3-319-57304-5
_2doi
050 4 _aQA184-205
072 7 _aPBF
_2bicssc
072 7 _aMAT002050
_2bisacsh
072 7 _aPBF
_2thema
082 0 4 _a512.5
_223
100 1 _aBeilina, Larisa.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aNumerical Linear Algebra: Theory and Applications
_h[electronic resource] /
_cby Larisa Beilina, Evgenii Karchevskii, Mikhail Karchevskii.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXIV, 450 p. 15 illus., 14 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPreface -- 1. Preliminaries -- 2. Vector Spaces -- 3. Inner Product Spaces -- 4. Linear Operators -- 5. Canonical Forms and Factorizations -- 6. Vector and Matrix Norms -- 7. Elements of the Perturbation Theory -- 8. Solving Systems of Linear Equations -- 9. Numerical solution of Linear Least Squares Problems -- 10. Algorithms for the Nonsymmetric Eigenvalue Problem -- 11. Algorithms for Solution of Symmetric Eigenvalue problem -- 12. Introduction to Iterative Methods for Solution of Linear Systems -- A. Matlab Programs -- References.
520 _aThis book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems.Developed from a number of courses taught repeatedly by the authors, the material covers topics like matrix algebra, theory for linear systems of equations, spectral theory, vector and matrix norms combined with main direct and iterative numerical methods, least squares problems, and eigen problems.Numerical algorithms illustrated by computer programs written in MATLAB® are also provided as supplementary material on SpringerLink to give the reader a better understanding of professional numerical software for the solution of real-life problems.Perfect for a one- or two-semester course on numerical linear algebra, matrix computation, and large sparse matrices, this text will interest students at the advanced undergraduate or graduate level.
650 0 _aMatrix theory.
650 0 _aAlgebra.
650 1 4 _aLinear and Multilinear Algebras, Matrix Theory.
_0http://scigraph.springernature.com/things/product-market-codes/M11094
700 1 _aKarchevskii, Evgenii.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aKarchevskii, Mikhail.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319573021
776 0 8 _iPrinted edition:
_z9783319573038
776 0 8 _iPrinted edition:
_z9783319861272
856 4 0 _uhttps://doi.org/10.1007/978-3-319-57304-5
912 _aZDB-2-SMA
999 _c448642
_d448642
942 _cEB
506 _aAvailable to subscribing member institutions only. Доступно лише організаціям членам підписки.
506 _fOnline access from local network of NaUOA.
506 _fOnline access with authorization at https://link.springer.com/
506 _fОнлайн-доступ з локальної мережі НаУОА.
506 _fОнлайн доступ з авторизацією на https://link.springer.com/