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Catalog description
Numerical Optimization, Newton's Methods for nonlinear equations and unconstrained optimization. Global methods, nonlinear least squares, integral equations.
Prerequisites 1. Math 524 (Linear Algebra)

2.
Math 542 (Numerical Solution of Differential Equations), or
 2. Math 543 (Numerical Matrix Analysis)
Computational Resources:
You must have access to a somewhat modern version of Matlab, or some other computational environment that you are comfortable using.
Students with Disabilities:
If you are a student with a disability and believe you will need accommodations for this class, it is your responsibility to contact Student Ability Success Center at (619)5946473. To avoid any delay, please contact Student Ability Success Center as soon as possible. Please note that accommodations are not retroactive, and cannot be provided until an accommodation letter from Student Disability Services is received by the Professor.
Required Text and Reading Materials:
Numerical Optimization (second edition), Jorge Nocedal and Stephen J. Wright, SpringerVerlag, Springer Series in Operations Research, 2006 ISBN 0387303030.
Errata: [1st Edition, 1st Printing], [1st Edition, 2nd Printing], [2nd Edition]
Class web page [http://terminus.sdsu.edu/SDSU/Math693a/], and handouts.
Course Outline (as of 7/8/2018):
Nocedal/Wright: 1Introduction, 2Fundamentals
of Unconstrained Optimization, 3Line Search Methods, 4TrustRegion
Methods, 5Conjugate Gradient Methods, 6Practical Newton Methods,
8QuasiNewton Methods, 10Nonlinear LeastSquares Problems,
11Nonlinear Equations.
[To Be Revised]
Professor
Peter Blomgren
blomgren DOT peter AT gmail DOT com
Class hours: MW 2:00p – 3:15p,
GMCS421
Office hours: TBA (GMCS587), and by appointment.