Concise Introduction to Linear Algebra
Auteur : Hu Qingwen
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.
Vectors and linear systems. Solving linear systems. Vector spaces. Orthogonality. Determinants. Eigenvalues and Eigenvectors. Singular value decomposition.
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.
Date de parution : 09-2020
15.6x23.4 cm
Date de parution : 09-2017
15.6x23.4 cm
Thèmes de Concise Introduction to Linear Algebra :
Mots-clés :
Elementary Row Operation; Reduced Row Echelon Form; vectors; Basic Feasible Solution; linear systens; Vector Space; determinants; Representation Matrix; orthogonality; Transition Matrix; eigenvalues and eigenvectors; Permutation Matrix; vector spaces; Row Echelon Form; Column Space; Real Matrix; Linearly Independent; Row Operations; Orthogonal Matrix; Jordan Normal Form; Jordan Chain; Jordan Blocks; Jordan Basis; Simplex Tableau; Initial Basic Feasible Solution; Linear Programming Problem; QR Decomposition; LU Decomposition; Linear Operator; Simplex Method; Finite Dimensional