Course detail

Computer Science

FSI-1IN-KAcad. year: 2021/2022

The course deals with selected of software modeling tools, which are often used in engineering practice. The variables, commands, data import/export, drawing, procedures and functions are presented and rules of program developing are demonstrated in Matlab language. Matlab capabilities are illustrated with examples of simple models of technical systems and technological processes.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. Ing. Radomil Matoušek, Ph.D.

Department

Institute of Automation and Computer Science (ÚAI)

Learning outcomes of the course unit

Students will acquire the basic knowledge of modeling technical systems and technological processes. They will gain experience with solving problems using tools of Matlab/Octave. Students will learn the basics of imperative programming.

Prerequisites

The usual secondary school computer literacy is supposed.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.

Assesment methods and criteria linked to learning outcomes

The maximum achievable score 100b (ECTS). Partial e-tests (6 tests up to 10 points), final test (max. 40 points). For passing the course it is necessary at least 50 points, including at least 20 points from e-tests and 10 points from the final test. Moreover, none of the sub-examples of the final test will have a score below 2 points.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The aim is to acquire the use of computers to solve problems focused to technical systems and processes modeling.

Specification of controlled education, way of implementation and compensation for absences

The attendance at lectures is recommended while at seminars it is obligatory. Education runs according to week schedules. The form of compensation of missed seminars is fully in the competence of a tutor.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Etter, D.M.: Introduction to MATLAB, Pearson, 2015.
Palm, W.J.: Introduction to MATLAB for Engineers, McGraw-Hill Education, 3.vydání, 2010.
Siauw, T., Bayen, A.: An Introduction to MATLAB Programming and Numerical Methods for Engineers, Academic Press, 2014.
The MathWorks Inc.: MATLAB version: R2024a (dokumentace), Natick,Massachusetts, 2024. https://www.mathworks.com

Recommended reading

Hanselman, D. C.: Mastering Matlab 6: A Comprehensive Tutorial and Reference, 2001.
Karban, P.: Výpočty a simulace v programech Matlab a Simulink, Computer Press, 2006.
Sedgewick, R., Wayne, K.: Algorithms, Addison-Wesley, 4. vydání, 2016.
Wengrow, J.: A Common-sense Guide to Data Structures and Algorithms, Pragmatic Bookshelf, 2. vydání, 2020.
Wirth, N.: Algorithms and Data Structures, Prentice Hall, 1985.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme B-STR-K Bachelor's

    specialization STR , 1 year of study, winter semester, compulsory

Type of course unit

 

Guided consultation in combined form of studies

17 hod., compulsory

Teacher / Lecturer

doc. Ing. Jan Roupec, Ph.D.
RNDr. Jiří Dvořák, CSc.

Syllabus

1. Introduction to computer science and modelling, introduction to Matlab.
2. Vectors and matrices, matrix operations, matrix and index expressions.
3. Control structures.
4. Polynomials: representation, evaluation, visualisation, operations with polynomials.
5. Graph drawing: point graph in plane, curve in space, surfaces, discrete data graphs.
6. Input and output operations.
7. Functions I: built-in functions, user defined functions, parameter types.
8. Functions II: functions with multiple parameters and return values, recursive functions.
9. Text operations.
10. Symbolic computation. Numerical derivation and integration.
11. Practical engineering problem solving.
12. Introduction to object oriented programming.
13. Matlab toolboxes, final discussion.

Guided consultation

35 hod., optionally

Teacher / Lecturer

prof. Ing. Radomil Matoušek, Ph.D.

Syllabus

1. Matlab environment, simple expressions, operators and variables.
2. Matrices and matrix operations. M-scripts.
3. Control Structures I.
4. Control structures II.
5. Graphs. Polynomials.
6. Data Acquisition and Processing.
7. Input and output operations.
8. Function I.
9. Function II. Recursion.
10. Working with texts.
11. Symbolic calculations. Example of engineering task solution.
12. Final test.
13. Submission of semester project. Credit.

Elearning

eLearning: currently opened course