SylabUZ
| Course name | Numerical methods |
| Course ID | 11.9-WE-AutP-NM-Er |
| Faculty | Faculty of Computer Science, Electrical Engineering and Automatics |
| Field of study | WIEiA - oferta ERASMUS / Automatic Control and Robotics |
| Education profile | - |
| Level of studies | First-cycle Erasmus programme |
| Beginning semester | winter term 2018/2019 |
| Semester | 2 |
| ECTS credits to win | 4 |
| Course type | obligatory |
| Teaching language | english |
| Author of syllabus |
|
| The class form | Hours per semester (full-time) | Hours per week (full-time) | Hours per semester (part-time) | Hours per week (part-time) | Form of assignment |
| Lecture | 15 | 1 | - | - | Credit with grade |
| Laboratory | 30 | 2 | - | - | Credit with grade |
to familiarize students with the basic numerical methods used in engineering calculations
forming understanding among students that it is necessary to correctly perform computer calculations that guarantee acceptable errors
shaping basic skills of a practical application of numerical methods in computer calculations - using the Matlab package
Mathematical analysis, Linear algebra with analytical geometry
Computer arithmetic: fixed and the floating-point representation of numbers, calculation errors in the floating-point arithmetic, stability, and correctness of a numerical algorithm, conditioning of a numerical task).
Solving nonlinear equations: bisection method, falsi rule, secant and tangent methods, multiple zeros, systems of nonlinear equations.
Solving problems of linear algebra: exact methods for solving systems of linear equations: Gauss method, pivoting, triangular distribution, Thomas method, Cholesky-Banachiewicz method; iterative methods: Jordan, Gauss-Seidel, determination of determinants and inverse matrix, spectral problem.
Interpolation: definition and classification of methods, polynomial interpolation: Lagrange interpolation formula, Newton interpolation formula; trigonometric interpolation, interpolation with spline functions, cubic spline.
Approximation: discrete and continuous mean square approximation, triangular families of orthogonal polynomials in approximation.
Quadratures: a complex pattern of rectangles and triangles, Newton-Cotes quadrature, Gaussian quadrature, numerical integration of integrals with improper boundaries, and with singular points inside the integration interval, integration of multidimensional functions.
Ordinary differential equations: Euler method, Rung-Kutta methods. Introduction to boundary problem methods and partial differential equations.
Matlab engineering calculations environment.
Lecture: traditional lecture
Laboratory: lab exercises
| Outcome description | Outcome symbols | Methods of verification | The class form |
Wykład - warunkiem zaliczenia jest uzyskanie pozytywnej oceny z kolokwium zaliczeniowego w formie pisemnej
Laboratorium - warunkiem zaliczenia jest uzyskanie pozytywnych ocen ze wszystkich ćwiczeń laboratoryjnych, przewidzianych do realizacji w ramach programu laboratorium
Składowe oceny końcowej = wykład: 50% + laboratorium: 50%
Modified by dr hab. inż. Wojciech Paszke, prof. UZ (last modification: 29-04-2020 11:49)
