CMSC/AMSC/MAPL 460 Computational Methods
Class: T, Th......12:30pm1:45 pm (CSI 2107)
Instructor: Ramani Duraiswami Email: ramani AT umiacs.umd.edu;
Office Hours: Wednesdays 1:30 p.m.  3:00, in AVW 3361. (you must confirm I am there before coming by emailing me)
TA: Ross Adelman; Email: rna AT umd.edu
Office Hours: 1:00 PM to 2:30 PM on Fridays, in AVW 3368
Textbook (Required): Numerical Computing with MATLAB, by Cleve Moler, ISBN 0898715601
Individual Chapters may be downloaded from the author's web site at http://www.mathworks.com/moler/chapters.html
The book may be purchased from the bookstore, or from the web.
Textbook (other): A useful reference is Ascher & Greif
Software (required): MATLAB.
You will need reliable access to MATLAB and a printer for doing homework in this course.
If you do not have access to Matlab and have a PC, the best option would be to buy the student edition from the bookstore.
You can also get by without buying this copy and using the software which should be accessible from University computers. However, this requires a degree of computer savviness, and your are responsible for figuring this out ASAP. Moreover, the system tends to be slow.
PIAZZA for peertopeer discussions/assistance.
NO LAPTOPS IN CLASS
Printing: Most homework will call for printing material (graphs, programs and the like off Matlab) and submitting it.
Emailed homework is NOT acceptable.
Prerequisites: Programming, advanced calculus, linear algebra.
Description in the catalog: Basic computational methods for interpolation, least squares, approximation, numerical quadrature, numerical solution of polynomial and transcendental equations, systems of linear equations and initial value problems for ordinary differential equations. Emphasis on methods and their computational properties rather than their analytical aspects.
Homework will be given out periodically, and will be due on the first class in the following week from the date handed out. No late homework, without prior arrangement. Homework will be posted on this web page.
Collaboration Policy: You may study together and discuss problems and methods of solution with each other to improve your understanding. You are welcome to discuss assignments in a general way among yourselves, but you may not use other students' written work or programs. Use of external references for your work should be cited. Clear similarities between your work and others will result in a grade reduction for all parties. Flagrant violations will be referred to appropriate university authorities.
You are responsible for checking this page.
Policy: Honor code http://www.studenthonorcouncil.umd.edu/code.html
Grading: Homework 30%, MidTerm 25%, Final 35%, Participation 10%
Previous versions of this course: (for reference) Fall2005 Spring2007 Fall 2008 Spring 2010
LECTURE 
CONTENTS 

1/24/2013 (Thursday) 

Introduction to the course. Why study Computational Methods? Rules. Syllabus

1/29/2013 (Tuesday) 
Lecture 2 Matlab 
Introduction to MATLAB. Ways to implement a matrix vector product 
1/31/2013 (Thursday) 
Lecture 3 
Representing numbers on a computer Overflow and conversion errors 
02/05/2013 (Tuesday) 
Lecture 4  IEEE754 floating point 
Homework 1  See Piazza  
02/07/2013 (Thursday)  Lecture 5  Matrices vectors Book 
02/12/2013 (Tuesday)  Lecture 6  Gaussian Elimination 
02/14/2013 (Thursday)  Lecture 7  LU 
Homework 2  See Piazza  
02/19/2013 (Tuesday)  Lecture 8  LU wrapup 
02/21/2013 (Thursday)  Lecture 9 LU Lecture 9 Interp  Homework Discussion (LU). Polynomial interplation 
02/26/2013 (Tuesday)  Lecture 10  Polynomial interplation (Newton and Lagrange forms) Book 
02/28/2013 (Thursday)  Lecture 11  Newton form and error analysis of polynomial interpolation 
03/05/2013 (Tuesday)  Lecture 12 Matlab  Errors in high order polynomial interpolation Local interpolation, linear splines 
03/07/2013 (Thursday)  Lecture 13  Cubic Spline Interpolation 
03/12/2013 (Tuesday) 
Review  
03/14/2013 (Thursday)  Exam  See Piazza for solution 
03/19/2013 (Tuesday)  Spring Break  
03/21/2013 (Thursday)  Spring Break  
03/26/2013 \ (Tuesday)  Lecture 14  Bisection, Newton and Secant Book 
03/28/2013 (Thursday)  Lecture 15  Convergence, golden search 
04/02/2013 (Tuesday)  Lecture 16  Wrap up of Lecture 15. Begin Least Squares. Normal Equations Book 
04/04/2013 (Thursday)  Lecture 17  Least Squares via QR decomposition 
04/09/2013 (Tuesday)  Lecture 18 Matlab  Computing the QR decomposition via Givens Rotations 
04/11/2013 (Thursday)  Review  
04/16/2013 (Tuesday)  Exam  
04/18/2013 (Thursday)  Lecture 20 Matlab  Householder transforms 
Course Eval  Course evaluation  
04/23/2013 (Tuesday)  Lecture 21  Eigenvalues and Eigenvectors Book 
04/25/2013 (Thursday)  Lecture 22 Matlab  Algorithms to compute Eigenvalues and Eigenvectors 
04/30/2013 (Tuesday)  Lecture 23 Matlab  The Singular Value Decomposition 
05/02/2013 (Thursday)  Lecture 24  Quadrature: Newton Rules, Error Book 
05/07/2013 (Tuesday)  Lecture 25  Quadrature: Romberg integration, Gaussian quadrature 
05/09/2013 (Thursday)  Lecture 26  Last Day of Classes! Review 
05/16/2013 (Thursday)  Final Exam 1:30  3:30 p.m.  In class 