CS 4210/Math 4250

Numerical Analysis and Differential Equations

Fall 2014

Announcements | Syllabus | Assignments | Problem of the Day

**Instructor**:
Charles Van Loan, 423 Gates,
255-5418, cv@cs.cornell.edu. 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.