CS3113 -  Numerical Methods Fall 2003

Course Objectives

Numerical Methods with MATLAB, by Gerald Recktenwald, Prentice Hall, 2000.

There are a number of resources available at the textbook's website: http://www.me.pdx.edu/~gerry/nmm/
 

Instructor

Eric Aubanel
Office: GW-E108
Hours: When my door is open, or by appointment
E-mail: aubanel@unb.ca
 

Schedule

MWF 11:30 - 12:20
Room: GWD 124
 

Website

www.cs.unb.ca/profs/aubanel/cs3113
 

Lecture Notes

The lecture slides provided by the textbook author will be used as a basis for the material presented in class, but there will also be demonstrations and examples worked on in class, for which no notes will be made available. Therefore you are expected to attend lectures and take your own notes. There may be several situations, such as the section on numerical differentiation (which is not covered in the textbook) where separate notes will be provided.
 

Study Guides

I will be placing study guides online, based on those provided by the textbook's author.
 

Software

1. Primary: MATLAB 5.3 or higher is available on Novell on all ITS computers in the open labs, and in the ITC Windows lab in ITD414. Or you may want to own it yourself: the student version of MATLAB, which has all the functionality you need, is available for sale at the University Bookstore.
2. Secondary: GNU Octave is a high-level language, primarily intended for numerical computations. It is a free numerical analysis and visualization environment that is mostly compatible with MATLAB so you can download it onto to your home computer. Plotting is done using GNUPlot which is included in the download. This software is provided only as a convenience for students and is not supported by the Faculty. Students can work out their homework using GNU Octave but are advised to produce the final versions using MATLAB under Novell in the ITS open labs.
3. NMM toolbox: MATLAB routines discussed in the textbook make up this toolbox. It is installed with MATLAB on Novell, so you will be able to interactively execute all sample problems in the book, and apply/modify them to some assignment problems. You can also download the toolbox yourself from www.me.pdx.edu/~gerry/nmm/mfiles/.

1. Assignments, including the programming, are vital in order to appreciate many of the subtleties of the various numerical methods that you will study this term. It is important that you do the assignments on your own, although you may consult your peers or instructor for ideas when you are stuck. Submitted work must be your own. Please refer to section IX (Academic Offences) on page 49 of the 2003-2004 Undergraduate Calendar or online.
2. Students who disagree with their evaluation should resubmit their assignment to the instructor with a written explanation of the issue and a proposed remedy. Errors in addition should be reported directly to the instructor, in person, after class or by arrangment. Late assignments will be assessed for feedback, but no mark recorded, with the following exceptions:
• medical grounds
• compassionate grounds
• prior arrangments have been made with the instructor's approval
3. You must obtain a mark of 50% or more on the final exam in order to score higher than a 'D' in this course.
4. NO CALCULATORS will be allowed on the midterms OR the final exam.
5. The midterms and the final exam will be CLOSED BOOK tests.

The following approximate schedule will help you plan your readings from Recktenwald. Please note that this schedule is TENTATIVE!

 

Week	Date	Reading (Recktenwald)	Topics (with # of lectures)
1	Sep 8 - 12	Ch 1-4	Introduction (6):  Two Important Theorems from Calculus MATLAB
2	Sep 15 - 19	Ch 5	Floating Point Numbers  Finite Precision Arithmetic Truncation Error
3	Sep 22 - 26	Ch 6.1-6.4	Nonlinear Equations (6):  Fixed Point Iteration  Method of Bisection  Newton's Method
4	Sep 29 - Oct 3	Ch 6.5-6.7	Secant & Hybrid Methods Roots of Polynomials
5	Oct 6 - 10	Ch 7, 8.1, 8.2	Systems of Equations (7):  Review of Linear Algebra  Gaussian Elimination
6	Oct 13 - 17 Thanksgiving: Oct 13 Midterm 1 - Oct 15	Ch 8.3	Ill-Conditioned Systems  Condition Numbers
7	Oct 20 - 24	Ch 8.4, 8.5	LU Decomposition Cholesky Factorization Nonlinear Systems of Equations
8	Oct 27 - 31	Ch 9	Least Squares Fitting (3):  Normal Equation QR Factorization
9	Nov 3 - 7	Ch 10	Interpolation (3): Lagrange Interpolation  Newton Divided Differences Splines
10	Nov 10 - 14 Midterm 2 - Nov 14	Supplementary course notes	Numerical Differentiation (2):  Differences  Richardson Extrapolation
11	Nov 17 - 21	Ch 11	Numerical Integration (3):  Rectangular & Trapezoidal Rules  Simpson's Rule
12	Nov 24 - Nov 28	Ch 12	Differential Equations (3 or so):  Euler's Method Runge-Kutta Methods
13	Dec 1 - 3		tba

 
 
 
 

Revised: September 2, 2003 by Eric Aubanel