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010 _a 2019757259
020 _a9783319110790
024 7 _a10.1007/978-3-319-11080-6
_2doi
035 _a(DE-He213)978-3-319-11080-6
040 _aDLC
_beng
_epn
_erda
_cDLC
072 7 _aMAT002050
_2bisacsh
072 7 _aPBF
_2bicssc
072 7 _aPBF
_2thema
082 0 4 _a512.5
_223
_bAXL
100 1 _aAxler, Sheldon,
_eauthor.
_91986
245 1 0 _aLinear Algebra Done Right /
_cby Sheldon Axler.
250 _a3rd ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _a1 online resource (XVII, 340 pages 26 illustrations in color.)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUndergraduate Texts in Mathematics,
_x0172-6056
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.
588 _aDescription based on publisher-supplied MARC data.
650 0 _aAlgebra.
_91987
650 0 _aMatrix theory.
_91988
650 1 4 _aLinear and Multilinear Algebras, Matrix Theory.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M11094
_91989
776 0 8 _iPrint version:
_tLinear algebra done right
_z9783319110790
_w(DLC) 2014954079
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,
_x0172-6056
_91990
906 _a0
_bibc
_corigres
_du
_encip
_f20
_gy-gencatlg
942 _2ddc
_cBK
999 _c1448
_d1448