Course: Mathematics 4

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Course title Mathematics 4
Course code NTI/MA4
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Stebel Jan, doc. Mgr. Ph.D.
  • Exner Pavel, Ing. Ph.D.
Course content
Lectures: 1) Well known errors in software and their aftermath, introduction to finite precision computation, rounding errors in basic linear algebra operations. 2) Rounding errors in basic linear algebra operations, upper error bounds. 3) Direct solvers in finite precision arithmetic, LU decomposition, Cholesky decomposition, pivoting. 4) Inverse of a triangular matrix in finite precision arithmetic, Kahan matrix. 5) Iterative solvers - stationary iterative methods (Jacobi, Gauss-Seidel, SOR, ...). 6) QR decomposition in finite precision arithmetic - schemes of the Gram-Schmidt orthogonalization process, Givens rotation, Householder reflection. 7) Rank-revealing algorithms, overdetermined/underdetermined system of linear algebraic equations. 8) Eigen decomposition, singular decomposition, Moore-Penrose pseudoinverse. 9) Nonlinear equations and their systems. 10) Numerical derivatives, difference formulas, order of accuracy. 11) Interpolation, approximation, regression, extrapolation. 12) Interpolation, approximation, regression, extrapolation. 13) Numerical integration, quadrature formulas. 14) Time reserve. Tutorials: 1) Linear algebra repeating (matrix notation, matrix multiplication, equation with matrices,...). 2) Rounding errors in basic linear algebra operations, upper error bounds. 3) Direct solvers, LU decomposition, Cholesky decomposition, pivoting. 4) Inverse of a triangular matrix in finite precision arithmetic, Kahan matrix. 5) Iterative solvers - stationary iterative methods (Jacobi, Gauss-Seidel, SOR, ?) 6) QR decomposition in finite precision arithmetic - schemes of the Gram-Schmidt orthogonalization process, Givens rotation, Householder reflection. 7) Rank-revealing algorithms, overdetermined/underdetermined system of linear algebraic equations. 8) Eigen decomposition, singular decomposition, Moore-Penrose pseudoinverse. 9) Nonlinear equations and their systems. 10) Numerical derivatives, difference formulas, order of accuracy. 11) Interpolation, approximation, regression, extrapolation. 12) Interpolation, approximation, regression, extrapolation. 13) Numerical integration. 14) Time reserve.

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing)
  • Class attendance - 56 hours per semester
  • Preparation for exam - 44 hours per semester
  • Preparation for credit - 30 hours per semester
  • Preparation for formative assessments - 20 hours per semester
Learning outcomes
The subject extends theoretical knowledge, it aims to present as the overview of the numerical methods as their implementation aspects and interpretation of their results in the finite precision arithmetic. The course put emphasis on the usage of appropriate numerical methods in physics and engineering.
Student will obtain an integrated insight into properties of basic numerical methods. He will learn to critical assess the relevance of their results and have knowledge of weakness of selected implementations.
Prerequisites
Unspecified

Assessment methods and criteria
Combined examination

Requirements for getting a credit are activity at the tutorials and successful passing of the tests. Examination is written and oral form.
Recommended literature
  • Duintjer Tebbens E. J. ,Hnětynková I.,Plešinger M.,Strakoš Z.,Tichý P. Analýza metod pro maticové výpočty: Základní metody. Matfyzpress, 2012.
  • Nicholas J. Higham. Accuracy and Stability of Numerical Algorithms. 2002.
  • Segethová J. Základy numerické matematiky. Karolinum, 1998.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Mechatronics, Informatics and Interdisciplinary Studies Study plan (Version): Applied Sciences in Engineering (2019) Category: Special and interdisciplinary fields 2 Recommended year of study:2, Recommended semester: Summer