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====== IAM 961: Numerical Linear Algebra ======

Instructor: John Gibson, john.gibson@unh.edu\\
Office hours: Tue 2-3pm, Thu 12-1pm, 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.

Text: //Numerical Linear Algebra//, by Trefethen and Bau, SIAM Press.

[[gibson:teaching:fall-2014:iam961:outline | Course outline]]

[[gibson:teaching:fall-2014:iam961:grades | Grades ]]

^ lecture notes ^ date ^
| [[gibson:teaching:fall-2014:iam961:svddemo | SVD demo ]]| 09/24 |

^ HW ^ due ^ topic ^ comments ^
| {{:gibson:teaching:fall-2014:iam961:iam961-hw1.pdf|HW1}} | 9/22 | norms | |
| [[gibson:teaching:fall-2014:iam961:iam-961-hw2 | HW2 ]] | 10/06 | SVD | |
| {{:gibson:teaching:fall-2014:iam961:iam961-hw3.pdf|HW3}} | 10/20 | QR algorithms |
| HW4 | 11/10 | |
| HW5 | 11/24 |
| HW6 | 12/08 | |

^ exam ^ date ^ comments ^
| final | t.b.d. | |
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