Problems in linear algebra are a part of a wide variety of scientific applications including the design of structures, the analysis of electrical networks, and the modeling of chemical processes among many others. This course will cover the analysis and implementation of the algorithms used to solve linear algebra problems in practice. We will study algorithms for linear systems solution, linear least squares problems, and eigenvalue and singular value problems. In each case, we will study the computational tools underlying the algorithm. We will also examine issues of problem sensitivity and algorithmic stability and ways to improve efficiency by taking advantage of special matrix structures. Other topics in this course will include programming tools for matrix computation, software packages, and parallel algorithms for numerical linear algebra.
Prerequisites for this course are a sound knowledge of basic linear algebra, experience in numerical computation, and programming experience.
Class meetings: 4:00-5:15pm MW, DUAN G1B35
Class website: Daily assignments are posted on the Schedule page.
Temporary file spot: Syllabus, Questionnaire.