Course detail

Computer Programming 1

FEKT-BPA-PP1Acad. year: 2023/2024

The whole course will be taught in Matlab environment (or its freeware alternatives). Students will learn matrix operations, logical and relation operators. Next, advanced data types (e.g. complex numbers, structures, cells), program controlling methods (if-elseif-else conditions, for and while cycles, switch-case structures) will be taught. Methods for program acceleration like vectorization and code optimization will be emphasized. Students will learn basics of object oriented programming and graphical user interface creation.

Language of instruction

English

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Ing. Petr Kadlec, Ph.D.

Department

Department of Radio Electronics (UREL)

Offered to foreign students

Of all faculties

Entry knowledge

The subject knowledge on the secondary school level is required.

Rules for evaluation and completion of the course

Students can earn a maximum of 36 points for active work in computer exercises and homework assignments, 30 points for midterm tests during the semester, and 34 points for an individual MATLAB project.
The definition of point-awarded activities and how it is to be carried out is set out in the annually updated course guarantor's statement.

Aims

Students should learn basics of programming and algorithms. The subject will be taught in Matlab, which is programming language oriented on algorithms (no variables allocation or memory management is needed in comparison to C language). Next, students should get used to good programming habits (atomization, code structure, comments, variable names etc.) After this course, student should be able to build their own toolbox with graphical user interface (GUI).
The graduate is able to:
1) Process matrix operations in Matlab.
2) Transform mathematical algorithms into Matlab functions.
3) Plot 2D a 3D functions.
4) Create Matlab applications with a graphical user interface.
5) Write well-arranged and understandable code according to programming conventions.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Cormen, Thomas H., et al. Introduction to algorithms. MIT press, 2009. (EN)
MATLAB Primer. Www.mathworks.com [online]. 3 Apple Hill Drive Natick, MA 01760-2098: The MathWorks, 2017 [cit. 2017-08-21]. Dostupné z: https://www.mathworks.com/help/pdf_doc/matlab/getstart.pdf (EN)
VALENTINE, D. T. a Brian D. HAHN. Essential MATLAB for engineers and scientists. 3rd ed. London: Butterworth Heinemann, 2007. (EN)

Recommended reading

Not applicable.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme BPA-ELE Bachelor's

    specialization BPA-ECT , 1 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Petr Kadlec, Ph.D.

Syllabus

1. Introduction, history of Matlab, alternatives, coding conventions, script.
2. Matrix creation, matrix operations, indexing, logical and relational operations.
3. Advanced data types (complex numbers, char, logical, structures, cell).
4. Program controls, conditions, cycles.
5. Functions- header, local vs. global variables and Workspace.
6. Algorithms - algorithm description, time/memory complexity, sorting algorithms.
7. Algorithms - data structures, paradigms - Brute force, Command and Conquer, Greedy algorithm, Dynamic programing, backtracking.
8. Functions - handle, vectorization, code optimization, bsxfun, arrayfun, cellfun.
9. Graphics – plotting options, tex commands.
10. File management – read and write.
11. GUI – graphical user interface, appdesigner interface.
12. GUI - graphical user interface and uicontrols.
13. OOP - class/object, properties and methods, constructor, set, get, inheritance, access, namespace, enumeration. 

Exercise in computer lab

39 hod., compulsory

Teacher / Lecturer

doc. Ing. Petr Kadlec, Ph.D.

Syllabus

1. Introduction, history of Matlab, alternatives, coding conventions, script.
2. Matrix creation, matrix operations, indexing, logical and relational operations.
3. Advanced data types (complex numbers, char, logical, structures, cell).
4. Program controls, conditions, cycles.
5. Functions- header, local vs. global variables and Workspace.
6. Algorithms - algorithm description, time/memory complexity, sorting algorithms.
7. Algorithms - data structures, paradigms - Brute force, Command and Conquer, Greedy algorithm, Dynamic programing, backtracking.
8. Functions - handle, vectorization, code optimization, bsxfun, arrayfun, cellfun.
9. Graphics – plotting options, tex commands.
10. File management – read and write.
11. GUI – graphical user interface, appdesigner interface.
12. GUI - graphical user interface and uicontrols.
13. OOP - class/object, properties and methods, constructor, set, get, inheritance, access, namespace, enumeration. 

Elearning

eLearning: currently opened course