450-2094/02 – Digital Signal Processing (DZS)
| 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 | | |
| | Study language | English |
| Year of introduction | 2019/2020 | Year of cancellation | |
| Intended for the faculties | FEI | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
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.
Teaching methods
Lectures
Individual consultations
Experimental work in labs
Summary
The course Digital Signal Processing builds upon the prerequisite course Signals and Systems, extending students' knowledge and, in particular, their skills in digital signal processing and its application in control and measurement systems.
The aim of the course is to expand basic theoretical and practical knowledge in the field of discrete and digital signal processing. Students will become familiar with signal analysis methods in both the time and frequency domains, correlation functions, basic converters (ADC/DAC), digital signal filtering, and signal processing methods using FIR and IIR filters.
A significant component of the course involves the practical implementation of algorithms in the MATLAB simulation software and their programming in microcontrollers, allowing students to understand the limits and capabilities of digital technologies. The curriculum also includes work with instrumentation and virtual instruments for signal measurement, visualization, and analysis.
The course is designed for students in Bachelor's degree programs at the Faculty of Electrical Engineering and Computer Science, VŠB–TUO, and provides a solid foundation for further study in control systems, signal analysis, and signal processing.
Compulsory literature:
[1] Macháček Z. Digital signal processing. Available at the teacher and on the web pages smak.vsb.cz.. Ostrava. 2017.
[2] Stranneby D. Digital Signal Processing: DSP and Applications. Newnes. Great Britain. 2001
Recommended literature:
[2] John G. Proakis, Dimitris G. Manolakis: Digital Signal Processing: Principles, Algorithms, and Applications, Pearson Education. 2014.
Additional study materials
Way of continuous check of knowledge in the course of semester
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.
E-learning
Materials are available at https://lms.vsb.cz/?lang=en
Other requirements
There are not defined other requirements for students.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures
1. Introduction to the course scope and review.
2. Discrete-time signal . Basic definitions, scope of study, digital signal.
3. Time-domain analysis of discrete-time signal focusing on basic signal parameters.
4. Correlation functions and time-domain analysis of discrete-time signal .
5. Frequency analysis of continuous-time signal .
6. Frequency analysis of discrete-time signal .
7. Transformation of analog signal to digital signal (Analog-to-Digital Conversion).
8. Transformation of digital signal to analog signal (Digital-to-Analog Conversion).
9. Converters for digital and analog signal transformation.
10. Basic system principles, methods, and techniques of digital signal processing.
11. Methods and techniques of digital signal filtering using FIR filters. Description of basic algorithms.
12. Methods and techniques of digital signal filtering using IIR filters. Description of basic algorithms.
13. Description and definition of signal noise.
Labs (Exercises)
1. Signals in the time domain – simulation and measurement using virtual instruments.
2. Signal measurement using instrumentation and virtual instrumentation.
3. Calculation of basic signal parameters – simulation and implementation in a microcontroller.
4. Calculation of signal correlation function – simulation and implementation in a microcontroller.
5. Frequency analysis using instrumentation and virtual instrumentation.
6. Discrete frequency analysis (DFT/FFT) – simulation and implementation in a microcontroller.
7. Analog-to-digital transformation (ADC) – simulation, implementation in a microcontroller, and measurement using instruments.
8. Digital-to-analog transformation (DAC) – simulation, implementation in a microcontroller, and measurement using instruments.
9. Simulation of converters for digital and analog signal transformation.
10. System application using simulation.
11. Implementation of FIR filters – simulation and microcontroller programming.
12. Implementation of IIR filters – simulation and microcontroller programming.
13. Test.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction