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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 | | [[gibson:teaching:fall-2014:iam961:iam-961-hw4 |HW4]] | 11/17 | conditioning, stability, and accuracy| | HW5 | 11/24 | | HW6 | 12/08 | | ^ exam ^ date ^ comments ^ | final | t.b.d. | |

gibson/teaching/fall-2014/iam961.1414686271.txt.gz · Last modified: 2014/10/30 09:24 by gibson