CMSC/AMSC/MAPL 460 Computational Methods

 

Fall 2005, Tuesdays and Thursdays, 2:00pm- 3:15pm (CSI 2107)

Office Hours: Monday 10-11:30 and Thursday 3:30-4:30 and by appointment, in AVW 3365.

 

Instructor: Ramani Duraiswami  E-mail: ramani AT umiacs.umd.edu;

 

Textbook (Required)Numerical Computing with MATLAB, by Cleve Moler, ISBN 0-89871-560-1

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.

 

Software (required): MATLAB.      
The university has site licenses to this software and you will need to figure out how you can access this. Registered students should have received email with details on class accounts.

 

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 one week from the date handed out. No late homework, without prior arrangement. Homework will be posted on this web page. You are responsible for checking this page.

Policy: Honor code http://www.studenthonorcouncil.umd.edu/code.html

Grading: Homework 40%, Mid-Term 25%, Final 35%

 

DATE

LECTURE

CONTENTS

09/1, 2005

(Thursday)

Lecture 1

 

Introduction to the course.

Rules. Introduction to MATLAB

Chapter 1

09/6, 2005

(Tuesday)

Lecture 2

 

 Homework 1

Chapter 1

Types of error.

Fixed point and floating point representations. Consequences.

 

09/8, 2005

(Thursday)

 

Lecture 3

Chapter 2

Vectors. Matrices. Storage. Access. Norms.

09/13, 2005

(Tuesday)

Lecture 4

 

 

Chapter 2

Norms, Cramer’s rule, Gauss Elimination, Triangular and permutation matrices, LU decomposition

09/15,2005

(Thursday)

 

Lecture 5

 

Homework 2

 LU decomposition. The need for pivoting. Condition numbers and sensitivity.

09/20, 2005

(Tuesday)

Lecture 6

 Polynomial Interpolation

09/22, 2005

(Thursday)

 

Lecture 7

 

MATLAB

 Piecewise polynomial interpolation

09/27, 2005

(Tuesday)

Lecture 8

 Finding zeros/solving nonlinear equations

09/29, 2005

(Thursday)

 

Lecture 9

 

Homework 3

Nonlinear Equations

10/4, 2005

(Tuesday)

Lecture 10

Least Squares

10/6, 2005

(Thursday)

 

Lecture 11

Least Squares/QR/SVD 

10/11, 2005

(Tuesday)

Lecture 12

Numerical Integration

10/13, 2005

(Thursday)

 

Lecture 13

Review of material

10/18, 2005

(Tuesday)

Lecture 14

Mid Term

10/20, 2005

(Thursday)

 

Lecture 15

Numerical integration: Romberg integration 

10/25, 2005

(Tuesday)

Lecture 16

 Gaussian quadrature

10/27, 2005

(Thursday)

Homework 4

 No class

11/1, 2005

(Tuesday)

Lecture 18

 Ordinary Differential Equations

11/3, 2005

(Thursday)

 

Lecture 19

  Ordinary Differential Equations

11/8, 2005

(Tuesday)

Lecture 20

  Ordinary Differential Equations

11/10, 2005

(Thursday)

 

Lecture 21

 Fast Fourier Transforms

11/15, 2005

(Tuesday)

Lecture 22

 

Homework 5

 Fast Fourier Transforms

11/17, 2005

(Thursday)

 

Lecture 23

 FFT wrapup. Eigenvalues and Eigenvectors

11/22, 2005

(Tuesday)

Lecture 24

 Eigenvalues and Eigenvectors

11/24, 2005

(Thursday)

 

No Class  (Thanksgiving)

 

11/29, 2005

(Tuesday)

Lecture 25

 Eigenvalue decomposition and SCD

12/1, 2005

(Thursday)

 

Lecture 26

 Review

12/6, 2005

(Tuesday)

Lecture 27

 No class

12/8, 2005

(Thursday)

 

Lecture 28

 No class

12/13, 2005

(Tuesday)

Lecture 29

 Review

12/19, 2005

(Monday)

Final Exam

10:30am-12:30pm

Tentative (subject to change)


Useful Links

Previous versions of 460 offered.

Prof. O'Leary: Fall 2002

Prof. Elman: 

 MATLAB resources:

  Introductory Tutorials

MATLAB tutorial from University of Utah

MATLAB tutorial from Carnegie Mellon University

MATLAB tutorial from Indiana University

  Slightly more advanced Tutorials

  More complete references/tutorials/FAQs