Math 573: Matrix Theory and Computations

Lectures: WF 8:00-9:15 in TAC 208
Instructor: Carmeliza Navasca, (cnavasca@clarkson.edu), SC 391
Office Hours: W 14:00-15:00, 16:00-17:00 and F 9:15-11:15

Objectives:
(1) to learn matrix theory which have important applications in engineering and other branches of mathematics
(2) to learn the fundamental concepts and algorithms of numerical linear algebra
(3) to acquire matrix based computational experiences

Course Info

Textbook: Gene H. Golub and Charles Van Loan, Matrix Computations, Third Edition, The Johns Hopkins University Press.

Prerequisites: Some knowledge of Linear Algebra and Matlab.

Grading Scheme: 50% hw, 15% final project, and 35% final exam

Homework: Weekly assignment will be collected every Friday at the beginning of class. Some problems will require some amount of Matlab programming. No late hw will be accepted.

Project: There will be a final project. More details later.

Exam: There is one comprenhensive exam TBA. No make-up exam will be given unless you have proper documentation. No shows on exams will result on an F grade.

Handouts and Other Info: All other info can be found at moodle.

Course Syllabus

(1) Review basic linear algebra concepts, computer arithmetic and error analysis, vector and matrix norms
(2) Direct solutions to linear systems: e.g. Gaussian, LU decomposition
(3) Linear least-squares problems: e.g. QR, SVD
(4) Eigenvalue problems
(5) Iterative solution of linear systems
(6) Introduction to multilinear algebra (tensors)