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Numerical Algorithms

Description

COURSE OBJECTIVES

This course brings fundamental mathematical concepts to life by studying concrete examples of important everyday problems and explaining how they are solved by numerical algorithms. The students will understand the theoretical background of these methods, learn how to implement them, and experience the practical aspects.

 

COURSE DESCRIPTION
We cover some key numerical algorithms for real-world applications, like GPS localization, TrueType fonts, robotic motion, Google’s PageRank, and JPEG compression. After going through some preliminary basics (Newton's root finding method, direct and iterative methods for solving linear systems, polynomial interpolation), we are ready to discuss the algorithms above, which are based on the concepts of least squares, Bézier curves, quadrature, eigenvalues, and the discrete cosine transformation, respectively.

 

LEARNING METHODS
The topics will be presented in the form of lectures and tutorials. Homework assignments with theoretical and practical programming exercises will be handed out, graded, and discussed.

 

EXAMINATION INFORMATION
The course grade is determined by the results of the homework assignments (50%) and the written final exam (50%).

 

REFERENCES

  • Timothy Sauer. Numerical Analysis. Second Edition. Pearson, 2012 Additional material will be provided through the course homepage.

People

 

Hormann K.

Course director

Fuda C.

Assistant

Ramanantoanina A.

Assistant

Additional information

Semester
Fall
Academic year
2020-2021
ECTS
6
Language
English
Education
Master of Science in Artificial Intelligence, Core course, Lecture, 1st year (3 ECTS)
Master of Science in Computational Science, Elective course, Lecture, 2nd year
Master of Science in Informatics, Elective course, Lecture, 1st year
Master of Science in Informatics, Elective course, Lecture, 2nd year