Instructor: John Gibson, Kingsbury N309E, john.gibson@unh.edu
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 speed 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.
lecture stuff | comments |
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svddemo.m |