| Numerical Analysis - 13538 - CS 51400 - LE1 |
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Associated Term: Spring 2023
Levels: Undergraduate, Graduate, Professional West Lafayette Campus Lecture Schedule Type Learning Outcomes: The course will provide an introduction to the foundational algorithms in what is now called Scientific Computing. We will cover the topics traditionally included in such a course at the graduate level, with the exception of topics in numerical linear algebra (matrix computations), discussed in CS 515, and numerical optimization, discussed in CS 520. An undergraduate version of this course is available as CS314, and for students from disciplines other than CS and Mathematics, this might be more suitable depending on your previous knowledge of this material. Pre-requisites for this course would be knowledge of numerical algorithms (e.g., solution of linear and nonlinear equations, polynomial interpolation, least-squares data fitting) at the undergraduate level. You should be comfortable programming in one of Matlab, Python or Julia; I will use Matlab for teaching and for giving Homework problems. The topics discussed will include: Floating point arithmetic, the IEEE floating point standard Condition of problems, stability of algorithms Solution of nonlinear equations Algorithmic differentiation Polynomial interpolation Piecewise polynomial interpolation, splines Approximation of functions Numerical integration Numerical solution of ordinary differential equations Required Materials: Uri Ascher and Chen Greif, A First Course in Numerical Methods, Society for Industrial and Applied Mathematics, 2011. (ISBN 978-0-898719-97-0) Technical Requirements: View Catalog Entry
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