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001 978-3-319-11080-6
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020 _a9783319110806
_9978-3-319-11080-6
024 7 _a10.1007/978-3-319-11080-6
_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 _aAxler, Sheldon.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931986
245 1 0 _aLinear Algebra Done Right
_h[electronic resource] /
_cby Sheldon Axler.
250 _a3rd ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXVII, 340 p. 26 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUndergraduate Texts in Mathematics,
_x2197-5604
520 _aThis best-selling textbook for a second course in linear algebra is aimed at undergrad math majors and graduate students. The novel approach taken here banishes determinants to the end of the book. The text focuses on the central goal of linear algebra: understanding the structure of linear operators on finite-dimensional vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. The third edition contains major improvements and revisions throughout the book. More than 300 new exercises have been added since the previous edition. Many new examples have been added to illustrate the key ideas of linear algebra. New topics covered in the book include product spaces, quotient spaces, and dual spaces. Beautiful new formatting creates pages with an unusually pleasant appearance in both print and electronic versions. No prerequisites are assumed other than the usual demand for suitable mathematical maturity. Thus the text starts by discussing vector spaces, linear independence, span, basis, and dimension. The book then deals with linear maps, eigenvalues, and eigenvectors. Inner-product spaces are introduced, leading to the finite-dimensional spectral theorem and its consequences. Generalized eigenvectors are then used to provide insight into the structure of a linear operator.
650 0 _aAlgebras, Linear.
_94004
650 1 4 _aLinear Algebra.
_92159
710 2 _aSpringerLink (Online service)
_931987
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319110790
776 0 8 _iPrinted edition:
_z9783319110813
776 0 8 _iPrinted edition:
_z9783319307657
776 0 8 _iPrinted edition:
_z9783319939025
830 0 _aUndergraduate Texts in Mathematics,
_x2197-5604
_931988
856 4 0 _uhttps://doi.org/10.1007/978-3-319-11080-6
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
942 _cEBK
999 _c75169
_d75169