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Concise Introduction to Linear Algebra

Autor Qingwen Hu
en Limba Engleză Hardback – 21 sep 2017
Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices quickly into more advanced topics including, LU decomposition, orthogonal decomposition, Least squares solutions, Gram-Schmidt process, eigenvalues and eigenvectors, diagonalizability, spectral decomposition, positive definite matrix, quadratic forms, singular value decompositions and principal component analysis. This book is designed for onesemester teaching to undergraduate students.
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Specificații

ISBN-13: 9781138044494
ISBN-10: 1138044490
Pagini: 230
Ilustrații: 12
Dimensiuni: 156 x 234 x 19 mm
Greutate: 0.45 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC

Cuprins

Vectors and linear systems. Solving linear systems. Vector spaces. Orthogonality. Determinants. Eigenvalues and Eigenvectors. Singular value decomposition.

Notă biografică

Qingwen Hu is Assistant Professor at the University of Texas at Dallas. His research interests include: dynamical systems; state-dependent delay differential equations and their applications in engineering and biology; equivariant degree theory and applications; nonlinear analysis; operations research.

Descriere

Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices quickly into more advanced topics including, LU decomposition, orthogonal decomposition, Least squares solutions, Gram-Schmidt process, eigenvalues and eigenvectors, diagonalizability, spectral decomposition, positive definite matrix, quadratic forms, singular value decompositions and principal component analysis. This book is designed for onesemester teaching to undergraduate students.