Course detail
Computer Science
FSI-1IN-KAcad. year: 2024/2025
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
Number of ECTS credits
Mode of study
Guarantor
Entry knowledge
Rules for evaluation and completion of the course
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. Furthermore, successful completion of MATLAB Onramp.
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.
Aims
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.
Study aids
Prerequisites and corequisites
Basic literature
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
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
Classification of course in study plans
Type of course unit
Guided consultation in combined form of studies
Teacher / Lecturer
Syllabus
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
Teacher / Lecturer
Syllabus
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