CS 4210/Math 4250
Numerical Analysis and Differential Equations
Announcements | Syllabus | Assignments | Problem of the Day
Instructor: Charles Van Loan, 423 Gates, 255-5418, email@example.com. Office hours are here.
TA: Zhengdi Shen. Office Hours in 657 Rhodes Hall, Wed (1:20-2:20), Thur (3:00-4:00), Fri (1:20-2:20)
Piazza: We will be using it to handle questions about the assignments.
Meeting Time & Place: TTh 1:25-2:40, Phillips 403
Prerequisites: 4 credits. MATH 2210 or MATH 2940 or equivalent and a CS 1 course in Matlab, Java, Python, C++, etc. Recommended but not necessarily essential: one additional mathematics course numbered 3000 or above. This course can be taken before or after CS 4220/Math 4260 which covers matrix computations and numerical optimization.
Description: Introduction to the fundamentals of numerical analysis: error analysis, approximation, interpolation, numerical integration. In the second half of the course, the above are used to build approximate solvers for ordinary and partial differential equations. Strong emphasis is placed on understanding the advantages, disadvantages, and limits of applicability for all the covered techniques. Matlab programming is required to test the theoretical concepts throughout the course.
Text: A First Course in Numerical Methods by Ascher and Greif. OnlineText: Introduction to Scientific Computing-A Matrix-Vector Approach Using Matlab by Charles Van Loan.The second text will serve as a kind of Matlab work book.
Grading: Matlab assignments (50%), Midterm (20%), Final Exam (30%). (Note: There will be seven Matlab assignments and we count the best six 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.)
Online Readings and Software:
1. NCM: The online book Numerical Computing with Matlab is a useful companion. Individual chapters can be downloaded from here. Matlab codes associated with the text are available here.
2. Chebfun: The Chebfun system is just like Matlab only instead of manipulating vectors it manipulates functions. The Chebfun guide and software are available here.(Not necessary to do this for a few weeks.)
3. AG: Matlab codes associated with the Ascher and Greif text (required) can be downloaded here.
4. CVL: Matlab codes associated with the CVL notes are available here:
Some Linear Algebra References: Gil Strang's MIT Linear Algebra course videos and text are excellent. So is Carl Meyer's Matrix Analysis and Applied Linear Algebra book.
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.