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Numerical Optimization, Newton's Methods for nonlinear equations and unconstrained optimization. Global methods, nonlinear least squares, integral equations.Prerequisites
- 1. Math 524 (Linear Algebra)
Math 542 (Numerical Solution of Differential Equations), or
- 2. Math 543 (Numerical Matrix Analysis)
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)594-6473. 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, Springer-Verlag, Springer Series in Operations Research, 2006 ISBN 0-387-30303-0.
Class web page [http://terminus.sdsu.edu/SDSU/Math693a/], and handouts.
Course Outline (as of 7/8/2018):
Nocedal/Wright: 1-Introduction, 2-Fundamentals
of Unconstrained Optimization, 3-Line Search Methods, 4-Trust-Region
Methods, 5-Conjugate Gradient Methods, 6-Practical Newton Methods,
8-Quasi-Newton Methods, 10-Nonlinear Least-Squares Problems,
[To Be Revised]