Advanced topics in numerical linear algebra (eigenvalue decomposition, QR/SVD factorization, etc).
|7 Jun 2010||MathWorks Classroom Resources Team||
This course, taught in Fall 2006 by Dr. Per-Olof Persson, offers an advanced introduction to numerical linear algebra. Topics include direct and iterative methods for linear systems, eigenvalue decompositions and QR/SVD factorizations, stability and accuracy of numerical algorithms, the IEEE floating point standard, sparse and structured matrices, preconditioning, linear algebra software. Problem sets require some knowledge of MATLAB.
Materials available at link - Problem sets or projects, Course outline or syllabus, Textbook recommendations, Downloadable code or data files.
Target audience: Graduate
Academic institution: Massachusetts Institute of Technology
Materials available: Problem sets or projects, Course outline or syllabus, Textbook recommendations, Downloadable code or data files