AMATH 352
SLN 1055, MWF 10:50-11:50, Guggenheim 306
(Prerequisites: MATH 126 or MATH 136: recommended: CSE 142)

Applied Linear Algebra and Numerical Analysis


Instructor:

 Brandon Bale
Guggenheim 410
tel:
fax: 685-1440
bbale@amath.washington.edu
office hours in GUG: W 2-3
office hours in MSCC: Th 2-3

Homework Grades 2003 Web Page
Course description Textbook Syllabus Objectives Handouts Schedule

Course Description

Development and application of numerical methods and algorithms to problems in the applied sciences and engineering. Applied linear algebra and introduction to numerical methods. Emphasis on use of conceptual methods in engineering, mathematics, and science.

Textbook

Available at the University Bookstore:

The matlab scripts that accompany this book are available on the PCs in the MSCC lab,
or can be downloaded from

Other references:

There are many other "numerical analysis" books that cover similar material. Here are a few:

Syllabus

(1) Review of Applied Linear Algebra: Basis, range, rank vector norms, matrix norms. Special matrices: symmetric, orthogonal, lower and upper triangular, tridiagonal.

(2) Solution of a Single Nonlinear Equation: Bisection method. Newton's method. Convergence to a root.

(3) Direct Methods for Solving Dense Systems of Linear Equations: Gaussian elimination with partial pivoting. Solution of triangular systems, multiple right hand sides. Tridiagonal systems.

(4) Interpolation: Polynomial interpolation by Lagrange polynomials. Cubic splines.

(5) Numerical Quadrature: Trapezoid and Simpson quadrature. Richardson extrapolation. Infinite limits of integration.

(9) Ordinary Differential Equations - Initial Value Problems: Euler's method. Accuracy and stability. Trapezoid method. Runge-Kutta method.

Learning Objectives and Instructor Expectations

The goal of this course is to introduce approximate numerical methods for solving mathematical problems that cannot be solved exactly be hand. Such problems arise constantly in science, engineering, finance and elsewhere. We will study several basic numerical algorithms, how to implement them, and how to analyze their behavior mathematically. Our main tool in numerical analysis for this course will be MATLAB. We will use this to solve interesting problems numerically.

Schedule and Homework

Follow links in the table below to obtain a copy of the homework in PostScript (.ps) or Adobe Acrobat (.pdf) format. You may also obtain here solutions to some of the homework and exam problems. An item shown below in plain text is not yet available. For additional information regarding viewing and printing the homework and solution sets, click here.

Homework and Exams Homework Due Date Homework Problem Sets Homework Solutions
First day of classes Monday, June 21
Homework #1 Friday, June 25
Homework #2 Friday, July 2
Independence Day Monday, July 5 No class
Homework #3 Friday, July 9
Homework #4 Monday, July 19
Homework #5 Monday, July 26
Midterm Friday, July 30 midterm review
Homework #6 Friday, August 6
Homework #7 Friday, August 13
Final (part I) Friday, August 20
Last day of quarter Friday, August 20 final review

Grading

There will be 6-7 weekly homework assignments, due each Friday in lecture except for the week of the midterm and the last week of class. Homework will be 50% of your final grade. There will be one in-class midterm, worth 20% of your final grade. The last week of class there will be a take-home final and an in-class final the last day of instruction. These two final assignment/test will be 30% of your final grade.

You may view your homework and exam grades on-line.

Handouts