Gurantor department | Department of Cybernetics and Biomedical Engineering | Credits | 4 |

Subject guarantor | Ing. Zdeněk Macháček, Ph.D. | Subject version guarantor | Ing. Zdeněk Macháček, Ph.D. |

Study level | undergraduate or graduate | Requirement | Optional |

Year | 3 | Semester | winter |

Study language | English | ||

Year of introduction | 2019/2020 | Year of cancellation | |

Intended for the faculties | FEI | Intended for study types | Bachelor |

Instruction secured by | |||
---|---|---|---|

Login | Name | Tuitor | Teacher giving lectures |

MAC37 | Ing. Zdeněk Macháček, Ph.D. | ||

SCH0175 | Ing. Miroslav Schneider |

Extent of instruction for forms of study | ||
---|---|---|

Form of study | Way of compl. | Extent |

Full-time | Credit and Examination | 2+2 |

The subject Digital Signal Processing provides a basis for further study in the field of digital signal processing and signal processing by digital filters, analyze digital signals.
The student will be able to work with discrete time signals, digital signals and he/she will be able to determine their basic characteristics, correlation functions, frequency spectra, digital signal filtration analyses. He/she will be able to use MATLAB program environment for signal analysis and he/she will be able to implement algorithms with selected microprocessor technologies usage.

Lectures

Individual consultations

Experimental work in labs

The subject Digital Signal Processing follows the subject of bachelor study dealing with continuous signal processing and system analyses (Signals and Systems).
The subject enables obtain knowledge of the theoretical basis of digital signal processing in the area of modern digital control and communication technology. The course focuses on theoretical knowledge, measurement and analysis of digital signals together with digital signal processing.
The student will be able to work with discrete time signals, digital signals and he/she will be able to determine their basic characteristics, correlation functions, frequency spectra, and he/she will be able to analyze the digital signal filtering. He/she will be able to use MATLAB for signal processing and he/she will be able to implement the algorithms with selected microprocessor technologies usage.
This subject is intended for students of bachelor study at Faculty of Electrical Engineering and Computer Science at VŠB - TU Ostrava.
Learning outcomes of the course is to provide basic knowledge for further study in the field of control systems, communication technology, electronics.

Macháček Z. Digital signal processing. Available at the teacher and on the web pages smak.vsb.cz.. Ostrava. 2017.
Stranneby D. Digital Signal Processing: DSP and Applications. Newnes. Great Britain. 2001

John G. Proakis, Dimitris G. Manolakis: Digital Signal Processing: Principles, Algorithms, and Applications, Pearson Education. 2014.

Student realizes projects No.1-10 from the part in laboratory exercises. Projects consist of signal processing, measurement, calculation and generation of signals using laboratory instrumentation, mathematical software, microcomputer technology.
The student will prepare 10 project protocols. For each protocol, student can obtain to 2 points. For all protocols, the student can get a maximum of 20 points. At the end of the semester, the student will pass the final test for which he / she can get up to 20 points. Conditions for obtaining a credit: The student has worked out and has been classified all the protocols and if he has realized a test and he has received a total of at least 15 points. Protocols are processed during the semester in the laboratory hours.
The course is finished by the final exam, which consists of a written part 0 - 50 points and oral part 0 - 10 points. In order to pass the exam, students must succeed in all parts of the examination.

There are not defined other requirements for students.

Subject has no prerequisities.

Subject has no co-requisities.

Lectures:
Basic distribution of signal types and basic definitions with focus on signals digitalization, definition of the studied problem with mathematical description and graphical expression of digital signal processing.
Transformation from analog signal to digital signal, basic algorithms of digital signal modulation.
Shannon and Kotelnikov theorem, impulse signal, renewal signal w (t) by filtering the impulse signal wI (t) by low pass filter,
Discrete time signal w [n]. Basic definitions, characteristics of digital signal
Correlation function of discrete time signal w [n], signal analysis in time domain
Frequency spectrum of the discrete time signal w [n]. DFT, FFT algorithms. Energy spectrum of discrete time signal w [n], spectrum of power with discrete time signal w [n].
Methods of digital signal filtration FIR filters. Basic algorithms description.
Methods of filtration of digital signal IIR filters. Basic algorithms description.
Methods of filtration of digital signal by frequency filtration. Basic algorithms description.
Principles of digital signal conversion to analog signal. Basic digital signal demodulation algorithms.
Exercises:
laboratory introduction. Analysis and implementation of signal algorithms by comparing analog, pulse, discrete and digital signals.
Implementation of transformation from analog signal to digital signal, basic digital signal modulation algorithms.
Shannon and Kotelnikov theorem, impulse signal, renewal signal w (t) by filtering the impulse signal wI (t) by low pass filter,
Implementation and analysis of signal parameters with discrete time signal w [n], digital signal.
Analysis of the correlation function of the discrete time signal w [n] in the time domain.
Implementation of frequency spectrum of discrete time signal w [n]. DFT, FFT algorithms. Spectrum of discrete time signal w [n], discrete time signal spectrum w [n] ..
Methods of digital signal filtration FIR filters. Implementation of basic algorithms.
Methods of filtration of digital signal by frequency filtration. Implementation of basic algorithms.
Methods of filtration of digital signal by frequency filtration. Implementation of basic algorithms.
Final exam. Termination of laboratories.

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Credit and Examination | Credit and Examination | 100 (100) | 51 |

Credit | Credit | 40 | 15 |

Examination | Examination | 60 | 11 |

Show history

Academic year | Programme | Field of study | Spec. | Zaměření | Form | Study language | Tut. centre | Year | W | S | Type of duty | |
---|---|---|---|---|---|---|---|---|---|---|---|---|

2021/2022 | (B0714A150002) Control and Information Systems | P | English | Ostrava | 3 | Optional | study plan | |||||

2020/2021 | (B0714A150002) Control and Information Systems | P | English | Ostrava | 3 | Optional | study plan | |||||

2019/2020 | (B0714A150002) Control and Information Systems | P | English | Ostrava | 3 | Optional | study plan |

Block name | Academic year | Form of study | Study language | Year | W | S | Type of block | Block owner | |
---|---|---|---|---|---|---|---|---|---|

V - ECTS - bc. | 2021/2022 | Full-time | English | Optional | 401 - Study Office | stu. block | |||

V - ECTS - bc. | 2020/2021 | Full-time | English | Optional | 401 - Study Office | stu. block |