CS 4220/Math 4260
Numerical Analysis: Linear and Nonlinear Problems
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Instructor: Charles Van Loan, 423 Gates, 255-5418, firstname.lastname@example.org. Office hours are here.
TAs: Hung Tran, email@example.com and Scott Wehrwein (firstname.lastname@example.org) . TA office hours are Tues 1-2 (Hung, Gates G15), Tue 2-3 (Scott, Gates G15), Thurs 1:30-2:30 (Hung, Malott 104 ), Thurs 11-12 (Scott, Gates G15).
Meeting Time & Place: Olin 245, MWF 2:30-3:20
Description: 4 credits. Prerequisites: MATH 2210 or 2940 or equivalent, one additional mathematics course numbered 3000 or above, and knowledge of Matlab programming. Introduction to the fundamentals of numerical linear algebra: direct and iterative methods for linear systems, eigenvalue problems, singular value decomposition. In the second half of the course, the above are used to build iterative methods for nonlinear systems and for multivariate optimization. Strong emphasis is placed on understanding the advantages, disadvantages, and limits of applicability for all the covered techniques. Computer programming is required to test the theoretical concepts throughout the course. This course can be taken before or after CS 4210/Math 4250.
Text: A First Course in Numerical Methods by Ascher and Greif. Chapters 1-9 pretty much cover what we do in the course.
Online Reading Materials: Introduction to Scientific Computing: A Matrix Vector Approach Using Matlab, C. Van Loan.
Some Linear Algebra References: Matrix Analysis and Applied Linear Algebra (C. Meyer), Linear Algebra and its Applications (G. Strang). An excellent online linear algebra course is available here.
Some Matlab References: Insight Through Computing: A Matlab Introduction to Computational Science and Engineering (Van Loan and Fan), Getting Started with Matlab 7 (Pratap), Matlab: An Introduction with Applications (Gilat), Mastering Matlab7 ( Hanselman & Littlefield)
Computing: MATLAB is available on all public CIT Machines. The student edition of MATLAB is available from Mathworks.
Grading: Matlab assignments (50%), Midterm (25%), Final Exam (25%). (Note: There will be eight Matlab assignments and we count the best seven scores. That way there is no issue if you are sick or travelling or have too much other stuff going on around a due date.)