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IAM 961 Numerical Linear Algebra

Instructor: John Gibson,
Lecture: MW 9:40-11:00am, Kingsbury N1332
Office hours: t.b.d. Kingsbury N309E, or after class

Numerical linear algebra is the science of solving systems of linear equations $Ax=b$ and the eigenvalue problem $A v = \lambda v$ on a digital computer –problems are at the root of the vast bulk of scientific computation. Compared to classical linear algebra, the finite precision and computational cost of numerical mathematics brings in a number of important new concepts, including conditioning, stability, and accuracy, and efficiency. We will develop these ideas and learn the most important numerical linear algebra algorithms: QR, LU, SVD decompositions, Gramm-Schmidt orthogonalization, the QR eigenvalue algorithm, and Krylov subspace methods. Time permitting, we will also study key algorithms for function optimization and the solution of systems of nonlinear equations.

This semester we will also be exploring the Julia scientific programming language. Julia is the future of scientific computing. Get on board now!

Text: Numerical Linear Algebra, by Trefethen and Bau, SIAM Press. I strongly recommend that you buy a paper copy of this book. It's only $50.

Course outline


Homework and exercises

Homeworks will be turned in a graded; exercises are work you should do but not turn in.

HW/EX due topic comments
ex1 getting started with Julia
hw1 W 09/14 linear algebra reviewish
hw2 M 10/03 SVD
HW3 M 11/21 QR, stability, accuracy Julia notebook how-to
gibson/teaching/fall-2016/iam961.txt · Last modified: 2016/11/04 12:03 by gibson