01354nam0 22003131i 450 UON0047599020231205105228.294978-83-04-05062-420170413d2012 |0itac50 bapolPL|||| 1||||CesarzRyszard Kapuścińskiopracowala Beata NowackaKatowiceUniwersytet Śląski ; WrocławZakład Narodowy im. Ossolińskich - Wydawnictwo2012. -cxxxviii198 p. ; 17 cm.Dono prof. De CarloIT-UONSI POLACCOCOLLBN1/0315001UON002885702001 Biblioteka Narodowa. Seria 1315PLWrocławUONL003154PLKatowiceUONL003315891.85Letteratura polacca21KapuscinskiRyszardUONV043630144732NOWACKABeataUONV228222Uniwersytet ŚląskiUONV266302650Zakład Narodowy Imienia OssolińskichUONV257947650ITSOL20260828RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEO E ARCHIVIO STORICOUONSIUON00475990SIBA - SISTEMA BIBLIOTECARIO DI ATENEO E ARCHIVIO STORICOSI COLL BN1 0315 SI 22110 7 0315 Dono prof. De CarloCesarz4824846UNIOR03597nam 22006135 450 991030011970332120260904222036.0981-13-0926-4978-981-13-0926-710.1007/978-981-13-0926-7(CKB)4100000005323365(DE-He213)978-981-13-0926-7(MiAaPQ)EBC6310767(PPN)186247575(UkBuK)1510322(EXLCZ)99410000000532336520180717d2018 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierLinear Algebra /by M. Thamban Nair, Arindama Singh1st ed. 2018.Springer Nature20181 online resource (XI, 341 p. 2 illus.)981-13-0925-6 Includes bibliographical references and index.Chapter 1. Vector Spaces -- Chapter 2. Linear Transformations -- Chapter 3. Elementary Operations -- Chapter 4. Inner Product Spaces -- Chapter 5. Eigenvalues and Eigenvectors -- Chapter 6. Block Diagonal Representation -- Chapter 7. Spectral Decomposition.This book introduces the fundamental concepts, techniques and results of linear algebra that form the basis of analysis, applied mathematics and algebra. Intended as a text for undergraduate students of mathematics, science and engineering with a knowledge of set theory, it discusses the concepts that are constantly used by scientists and engineers. It also lays the foundation for the language and framework for modern analysis and its applications. Divided into seven chapters, it discusses vector spaces, linear transformations, best approximation in inner product spaces, eigenvalues and eigenvectors, block diagonalisation, triangularisation, Jordan form, singular value decomposition, polar decomposition, and many more topics that are relevant to applications. The topics chosen have become well-established over the years and are still very much in use. The approach is both geometric and algebraic. It avoids distraction from the main theme by deferring the exercises to the end of each section. These exercises aim at reinforcing the learned concepts rather than as exposing readers to the tricks involved in the computation. Problems included at the end of each chapter are relatively advanced and require a deep understanding and assimilation of the topics.Algebras, LinearMatrix theoryAlgebraMathematicsStudy and teachingLinear Algebrahttps://scigraph.springernature.com/ontologies/product-market-codes/M11100Linear and Multilinear Algebras, Matrix Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/M11094Mathematics Educationhttps://scigraph.springernature.com/ontologies/product-market-codes/O25000Algebras, Linear.Matrix theory.Algebra.MathematicsStudy and teaching.Linear Algebra.Linear and Multilinear Algebras, Matrix Theory.Mathematics Education.551.48Nair M. Thambanauthttp://id.loc.gov/vocabulary/relators/aut767986Singh Arindamaauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910300119703321Linear Algebra1963845UNINA