Course detail

Mathematics 5 (K)

FAST-NAA022-AAcad. year: 2023/2024

Introduction to numerical mathematics, namely interpolation and approximations of functions, numerical differentiation and quadrature, analysis of algebraic and differential equations and their systems.

Language of instruction

English

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

prof. Ing. Jiří Vala, CSc.

Department

Institute of Mathematics and Descriptive Geometry (MAT)

Entry knowledge

Basic courses of mathematics for bachelor students, MATLAB programming (as in the recommended course at MAT FCE).

Rules for evaluation and completion of the course

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Aims

To understand basic principles of numerical computations and learn essential factors affecting numerical calculations. Be able to solve basic elementary problems of numerical mathematics. Iteration methods for the equation f(x)= 0, finite and iterative methods for the soulution of systems of linear equations, interpolation and approximation of functions, numerical differentiation and numerical integration, numerical methods for boundary-value differential problems.
The outputs of this course are the skills and the knowledge which enable the graduates understanding of basic numerical problems and of the ideas on which the procedures for their solutions are based. In their future practice they will be able to recognize the applicability of numerical methods for the solution of technical problems and use the existing universal programming systems for the solution of basic types of numerical problems and their future improvements effectively.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

QUARTERONI A., SACCO R., SALERI F.: Numerical Mathematics. Springer Berlin 2017.   (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme NPC-SIK Master's 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Petra Rozehnalová, Ph.D.

Syllabus

1. Errors in numerical computations. Contractive mappings, application to solution of nonlinear algebraic equations: simple iterative method, Newton method, method of secants. 2. Direct methods for solution of systems of linear algebraic equations, namely multiplicative decompositions: LU decomposition, Choleski decomposition, idea of QR decomposition. 3. Iterative and relaxation methods for solution of systems of linear algebraic equations, namely Jacobi and Gauss-Seidel methods including relaxation. 4. Conjugate gradient method, namely for systems of linear algebraic equations. Newton method for nonlinear systems. 5. Conditionality of systems of equations. Least squares method: idea, discrete case. 6. Lagrange interpolating polynomial, namely Newton form. Hermite interpolating polynomial. 7. Cubic splines: idea for Lagrange splines, calculations for Hermite splines. 8. Numerical differentiation. Finite difference method, application to boundary value problems for ordinary differential equations of order 2. 9. Numerical integration: rectangular, trapezoidal and Simpson rule, including approximation error estimate. Idea of more-dimensional numerical integration. 10. Finite element method, application to boundary value problems for ordinary differential equations of order 2. 11. Time-dependent problems: Euler explicit and implicit method, Crank-Nicolson method and Runge-Kutta methods, application to initial value problems for ordinary differential equations of order 1. 12. Continuation and completion of preceding themes, comments to engineering applications. 13. Finite element method for partial differential equations, example of equation of heat transfer.

Exercise

13 hod., compulsory

Teacher / Lecturer

doc. Ing. Vladislav Kozák, CSc.
Ing. Anna Derevianko

Syllabus

1.-2. Introduction to MATLAB: MATLAB environment, MATLAB online, assignment to variables, double dot, operations with number and vectors, plot, comments, MATLAB help, cycle for-end and condition if-else-end. Setting individual semester work. 3.-4. Repetition of methods for solution of 1 nonlinear equation: function graph and root estimate, script for 1 specific example and method of bisection, generalization for an arbitrary functions and initial inputs (for, if, plot, anonymous function). 5.-7. Implementation of iterative methods for solution of systems of linear algebraic equations: matrix operations (*, .*, +, inv, det, size and similar), vector norm, creation of solver with a lower triangular matrix, consequently creation of script for Gauss-Seidel method in matrix notation, creation of a function including check of inputs (diagonal dominance, etc.). 8.-9. Approximation of functions: least squares method in matrix form, usage of prepared Gauss-Seidel iteration for solution of a normal equation, Lagrange interpolation – form of a polynomial and setting coefficients, possible relation to numerical integration following composed rectangular rule. 11.-12. Ordinary differential equations: explicit and implicit Euler method for order 1, finite difference method for order 2, utilization of prepared solver of systems of linear algebraic equations, comparison with finite element method. 13. Evaluation of semester work.