Course Details
Numerical methods 1
Academic Year 2026/27
DAB030 course is part of 24 study plans
 DPA-V Summer Semester 1st year
 DPA-S Summer Semester 1st year
 DPA-M Summer Semester 1st year
 DPA-K Summer Semester 1st year
 DPA-GK Summer Semester 1st year
 DPA-E Summer Semester 1st year
 DKA-V Summer Semester 1st year
 DKA-S Summer Semester 1st year
 DKA-M Summer Semester 1st year
 DKA-K Summer Semester 1st year
 DKA-GK Summer Semester 1st year
 DKA-E Summer Semester 1st year
 DPC-V Summer Semester 1st year
 DPC-S Summer Semester 1st year
 DPC-M Summer Semester 1st year
 DPC-K Summer Semester 1st year
 DPC-GK Summer Semester 1st year
 DPC-E Summer Semester 1st year
 DKC-V Summer Semester 1st year
 DKC-S Summer Semester 1st year
 DKC-M Summer Semester 1st year
 DKC-K Summer Semester 1st year
 DKC-GK Summer Semester 1st year
 DKC-E Summer Semester 1st year
Credits
4 credits
Language of instruction
Czech
Semester
Course Guarantor
Institute
Forms and criteria of assessment
Entry Knowledge
Aims
Basic Literature
VITÁSEK E.: Základy teorie numerických metod pro řešení diferenciálních rovnic. Academia Praha 1994. (cs)
Offered to foreign students
Course on BUT site
Lecture
13 weeks, 3 hours/week, elective
Syllabus
- 1. Errors in numerical calculations. Numerical methods for one nonlinear equation in one unknown
 - 2. Basic principles of iterative methods. The Banach fixed-point theorem.
 - 3. Norms of vectors and of matrices, eigenvalues and eigenvectors of matrices. Iterative methods for systems of linear algebraic equations – part I.
 - 4. Iterative methods for linear algebraic equations – part II. Iterative methods for systems of nonlinear equations.
 - 5. Direct methods for systems of linear algebraic equations, LU-decomposition. Systems of linear algebraic equations with special matrice – part I.
 - 6. Systems of linear algebraic equations with special matrices – part II. The methods based on the minimization of a quadratic form.
 - 7. Computing inverse matrices and determinants, the stability and the condition number of a matrix.
 - 8. Eigenvalues of matrices – the power method. Basic principles of interpolation.
 - 9. Polynomial interpolation.
 - 10. Interpolation by means of splines. Orthogonal polynoms.
 - 11. Approximation by the discrete least squares.
 - 12. Numerical differentiation, Richardson´s extrapolation. Numerical integration of functions in one variables – part I.
 - 13. Numerical integration of functions in one variables – part II. Numerical integration of functions in two variables.