CS222: Introduction to Scientific Computation

Summer 1996

An introduction to elementary numerical analysis and scientific computation. Topics include interpolation, quadrature, linear and nonlinear equation solving, least-squares fitting, and ordinary differential equations. The Matlab computing environment is used. Vectorization, efficiency, reliability, and stability are stressed.

Class Information

Staff

Lectures

Class meets every day, M-F 1:00-2:15 in 205 Upson Hall.

Course Administration

Laurie Buck, 303 Upson, 255-3534.
All the questions concerning grade recording, accounts should be addressed to the course administrator.

Prerequisites

CS 100 and pre/corequisite of Math 221 or Math 293.

Course Materials

Text: Introduction to Scientific Computing: A Matrix-Vector Approach Using Matlab, by Charles Van Loan. It will be distributed in class.
Software: MATLAB. You can purchase Student Matlab, for either the MacIntosh or the PC version, though you do not have to.

Computer Labs

This course has been designated to use the three computer labs: B7 Upson, B8 Sibley, and G83 Martha Van Rensselaer.

Problem Sets

There will be 6 assignments which will be handed out in lecture or from this page. Extras will be available in rack outside Upson 303. Assignments will be collected in class. All the computing problems will be done in MATLAB. Return of graded work will be handled in class. An assignment is due at the beginning of the class on the due date. Late assignments won't be accepted for credit. The worst grade from the six assignments will be ignored for the final grade. Each assignment can be done alone or with at most one partner. Print your name (one copy with both names if working in pairs) on the first page and include your student ID. No change or addition of partner names after an assignment has been handed in.

Exams

There will be a midterm and a final exam. Days and times are listed below.

Grading

Your final total score will be computed as follows:
Best 5 assignments 40%, Midterm 30%, Final 30%. Your final grade will be assigned according to your relative ranking in the class based on your final total scores.

Syllabus-Calendar

June 24, M Introduction A 1 out
June 25, T Programming in MATLAB
June 26, W Errors
June 27, T Floating Point Numbers Registration Deadline
June 28, F Polynomial Interpolation
July 1, M Vandermonde/Newton A 1 due, 2 out
July 2, T Piecewise Interpolation
July 3, W Linear/Cubic Hermite
July 4, T No Class
July 5, F Cubic Splines Add Course Deadline
July 8, M Numerical Integration A 2 due, 3 out
July 9, T Newton-Cotes
July 10, W Composite Rules Change Credit/Grade Deadline
July 11, T Adaptive Quadrature
July 12, F Review A 3 due
Drop Course Deadline
July 15, M Midterm Exam, at the classroom A 4 out
July 16, T Matrices and Operations
July 17, W Linear Systems and LU
July 18, T Least Squares
July 19, F QR and Givens
July 22, M Cholesky A 4 due, 5 out
July 23, T Finding Roots
July 24, W Minimize Function of One Variable
July 25, T Minimize Multivariate Functions
July 26, F Solve Non-Linear Systems
July 29, M Initial Value Problems A 5 due, 6 out
July 30, T Euler /Backward Euler
July 31, W Runge-Kutta Methods
Aug. 1, T Adam Methods A 6 due
Aug. 2, F Review
Aug. 5, M No Class
Aug. 6, T Final Exam 10:30am at the classroom

Source Code Examples from Introduction to Scientific Computing

At the Mac labs B-7 Upson, B-8 Sibley and G-83 Martha van Rennselaer Hall, the source code is located at the folders: /Applications/MATLAB 4.2c.1/CS 222/Chapter.[1-9]

If you plan to work on your own stand alone computer or at a lab other than the assigned ones, here is the source code for the examples:

You need a postscript file viewer installed at your computer in order to see the files below.