- Department of Applied Mathematics
Students obtain fundamentals of model description, theory of finite-state automata and algorithms. Several numerical algorithms are explained and principles of their implementation are introduced.
- Syllabus of lectures:
1.Model development, mathematical description of models.
2.Finite-state automata, Turing machine.
3.Definition of an algorithm.
4.Solvability and complexity classes for problems on finite sets.
5.Iteration, piecewise constant interpolation.
6.Recurrence algorithms, chain fractions.
7.Numerical stability of a process.
8.Difference methods, stability of a solution.
9.Linear and non-linear algorithms.
10.Discrete fast algorithms.
11.Fast Fourier transformation.
12.Data organisation, fast convolution.
13.Maximum, minimum and optimum, complexity classes.
14.Implementation of discrete algorithms.
- Syllabus of tutorials:
- Study Objective:
- Study materials:
Ralston A.: A first course in numerical analysis, McGraw-Hill, 1965
Blahut R. E.: Fast Algorithms for Digital Signal Processing, Addison - Wesley Publishing Company, Inc., 1985
Chabert J. L.: A History of Algorithms, Berlin Heidlberg NewYork, Springer-Verlag, 1999
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: