Linear Algebra and Matrix Theory by Jimmie GilbertIntended for a serious first course or a second course in linear algebra, this book carries students beyond eigenvalues and eigenvectors to the classification of bilinear forms, normal matrices, spectral decompositions, the Jordan form, and sequences and series of matrices. The authors present the material from a structural point of view: fundamental algebraic properties of the entities involved are emphasized. The approach is particularly important because the mathematical systems encountered in linear algebra furnish a wealth of examples for the structures studied in more advanced courses. By taking a straight and smooth path to the heart of linear algebra, students will be able to make the transition from the intuitive developments of courses at a lower level to the more abstract treatments encountered later.
MATH 5210 - Linear Algebra and Matrix Theory
Bulletin ExploreCourses. MATH Applied Matrix Theory Linear algebra for applications in science and engineering: orthogonality, projections, spectral theory for symmetric matrices, the singular value decomposition, the QR decomposition, least-squares, the condition number of a matrix, algorithms for solving linear systems. MATH offers a more theoretical treatment of linear algebra. The focus of MATH is on algorithms and concepts; the focus of EE is on a few linear algebra concepts, and many applications. Instructors: Candes, E. PI ; Taylor, C. PI ; Velcheva, K.
All rights reserved. EEO Statement. Privacy Statement. A comprehensive community-engaged campus of the University of Tennessee System. MATH - Linear Algebra and Matrix Theory 3 Credit Hours Vector spaces, linear transformations, eigenvalue and similarity transformations, orthogonal and unitary transformations, normal matrices, Jordan form. University of Tennessee at Chattanooga.