MTH630 Functional Analysis is designed for students in mathematics,
natural sciences, computer science, engineering, and other fields. It
is a good course for graduate students of engineering and basic sciences
who would like to strengthen mathematical skills and knowledge.
The main topic of MTH629 is continuous optimization. Some specific
methods we will discuss include Steepest Descent, Newton and Quasi-Newton
methods, Trust-Region methods. There is some flexibility in the choice
of topics, and I plan to include certain topics depending on interest of
the registered students.
The requirements of the course are familiarity with linear algebra, advanced calculus, mathematical proofs, and programming in a computer language (matlab, mathematica, maple, C, fortran, etc.) Evaluation is based on homework (which will include programming problems), and a project which is to be presented at the end of the semester.
The main text is Numerical Optimization, by J. Nocedal and S. Wright, (Springer Verlag 1999). In addition to the main text, I will add supplementary material. The presentation of material is elementary. It begins with vector spaces, matrices, and norms, and the theory is gradually developed, and then it is followed by applications to optimization.
The topics listed here may be more than we can cover in one semester; some of the topics may be left out.
Other useful references are:
Practical Optimization, by P. Gill, W. Murray, and M. Wright.
Academic Press, 1981.
Numerical Methods for Unconstrained Optimization and Nonlinear Equations,
by J. Dennis and R. Schnabel. SIAM 1983.
Iterative Methods for Optimization, by C. T. Kelley. SIAM, 1999.
Practical Methods of Optimization, by R. Fletcher. Wiley,
1997.
Numerical Linear Algebra, by L.N. Threfethen and D. Bau. SIAM,
1997.