gibson:teaching:fall-2016:iam961

Instructor: John Gibson, john.gibson@unh.edu

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 and the eigenvalue problem 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.

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