18.330: Introduction to Numerical Analysis

Welcome to the bastard child of mathematics and computer science. Not every mathematics problem is amenable to pen and paper. Not every computer science problem reduces to sorting. This is a class about how to use calculation to do math, and how to use mathematics to understand calculations. We will bridge the gap between dt and delta-t. We will learn how to solve simultaneous equations without the matrix inverse. We will find roots without the quadratic equation. And we will do it all with precision and accuracy.


Instructor Ross A. Lippert
Prerequisites 18.03 or 18.034
Textbook Numerical Analysis, Burden and Faires, 8th edition
Coordinates Monday, Wednesday, and Friday 2pm in 2-132
Lecturers Ross Lippert
TAs Tong Hoon Suk
Grading 40% two exams, 60% homework, no final
Contact Email Office Office hours Phone
Ross lippert@math.mit.edu 2-335 WF4 617-253-7905
Tong Hoon tonghoon@math.mit.edu 2-091 none 617-452-5476

Programs: During the course of lecture I will often use MATLAB to demonstrate an idea. The programs I use for this will be available to students: program directory


News


Schedule

Class days in red , holidays in blue , reg/add/drop dates in green

February 2006

Su Mo Tu We Th Fr Sa
1 2 3 4
5 6 7 8 9 10 11
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28

March 2006

Su Mo Tu We Th Fr Sa
1 2 3 4
5 6 7 8 9 10 11
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28 29 30 31

April 2006

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1
2 3 4 5 6 7 8
9 10 11 12 13 14 15
16 17 18 19 20 21 22
23 24 25 26 27 28 29
30

May 2006

Su Mo Tu We Th Fr Sa
1 2 3 4 5 6
7 8 9 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 30 31

Lectures

Feb.08 Introduction
Feb.10 Computer arithmetic
Feb.13 Computer arithmetic II and a little MATLAB
Feb.15 Finding roots of an equation (bisection, Newton)
Feb.17 Finding roots of an equation (Secant, Regula Falsi)
Feb.21 Fixed points and acceleration
Feb.22 Interpolation with Lagrange polynomials
Feb.24 Newton form and divided differences
Feb.27 Newton form and Hermite interpolation
Mar.01 Cubic splines, Bernstein polynomials and Bezier splines
Mar.03 Differentiation and Richardson extrapolation
Mar.06 Integration basics
Mar.08 Integration tricks (Romberg's method)
Mar.10 Multiple and improper integrals
Mar.13 Gaussian quadrature
Mar.15 first exam
Mar.17 ODEs -- Euler and Taylor
Mar.20 ODEs -- single-step methods
Mar.22 ODEs -- implicit and multistep methods
Mar.24 ODEs -- symplectic methods
Apr.03 Linear systems -- solution and matrix 'inversion' (6.1-6.4)
Apr.05 Linear systems -- factorizations and special matrices (6.5-6.6)
Apr.07 Linear systems -- least squares QR algorithm (8.1,9.3)
Apr.10 Eigenvalues -- the power method and the QR method (9.1,9.2)
Apr.12 Eigenvalues -- the QR method in practice (9.4)
Apr.14 Eigenvalues -- the QR method demonstration
Apr.19 Eigenvalues -- special applications (companion matrices)
Apr.21 Where to find linear algebra software?
Apr.24 Norms and conditioning (7.1,7.4)
Apr.26 Iterative methods for linear solutions (7.2,7.3)
Apr.28 Conjugate gradient method (7.5)
May.01 Optimization -- one-dimensional, golden section
May.03 second exam
May.05 Chebyshev polynomials (8.3)
May.08 Orthogonal polynomials (8.2)
May.10 Approximation by rational functions (8.4)
May.12 Fast Fourier transform and convolution (8.5-8.6)
May.15 Optimization -- n-dimensional Nelder-Meade, steepest descent
May.17 Optimization -- Newton's method and conjugate gradient

Homework assignments

Your write-up should be clear, complete and concise. There is no need to turn in pages and pages of numbers. If you find yourself writing programs more than a page long, something is wrong. You should prune and edit your work to about one page per problem, while explaining clearly your approach and reasoning.

This this is not the sort of math course most students are used to, the first problem set will be weighted less, so that it can serve more as a guide as to how future homeworks should be done.

When it comes time to writing something up or producing a program to carry out a calculation, I want each of you to struggle individually and find the heart of the matter by yourselves. I am planning on assigning few enough problems that you will be able to have these growth experiences without it taking up too much of your time.

Cheating: given the weight on problem sets in this course, there is clear incentive to cheat. Let me outline where I stand.

There will be 6 problem sets in all. They will be weighted mostly the same (except the first).

A link might not work if the problem set has not been assigned. If a link fails and the problem set has been assigned, then email me.

Feb.21 Problem set #1
Mar.06 Problem set #2
Mar.22 Problem set #3
Apr.10 Problem set #4
Apr.24 Problem set #5
May.10 Problem set #6

Ross A. Lippert, instructor

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