Course
SMP - Signalprocessing using Matlab/Python and Microprocessors
PDF Course Catalog Deutsche Version: SMP
Version: 2 | Last Change: 11.09.2019 21:45 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben
| Long name | Signalprocessing using Matlab/Python and Microprocessors |
|---|---|
| Approving CModule | SMP_BaET, SMP_BaTIN |
| Responsible |
Prof. Dr. Harald Elders-Boll
Professor Fakultät IME |
| Level | Bachelor |
| Semester in the year | winter semester |
| Duration | Semester |
| Hours in self-study | 78 |
| ECTS | 5 |
| Professors |
Prof. Dr. Harald Elders-Boll
Professor Fakultät IMEProf. Dr. Uwe Dettmar Professor Fakultät IMEProf. Dr.-Ing. Christoph Pörschmann Professor Fakultät IME |
| Requirements | Basic procedural programming skills Basic knowledge of digital signal processing: Sampling Theorem, Digital Filter, Fourier Transform |
| Language | German and English |
| Separate final exam | Yes |
Literature
Welch, Wright, Morrow: Real-Time Digital Signal Processing (CRC Press)
Final exam
Details
In their projects students implement given methods for digital signal processing in small teams and thereby show their ability to develop signal processing applications for various purposes.For the final grade the poject work, the project results, the final project presentation and the written project report are evaluated and scored according to different criteria and the final grade is derived form the total score.
Minimum standard
50% of the maximum achievable total score.Exam Type
In their projects students implement given methods for digital signal processing in small teams and thereby show their ability to develop signal processing applications for various purposes.For the final grade the poject work, the project results, the final project presentation and the written project report are evaluated and scored according to different criteria and the final grade is derived form the total score.
Learning goals
Knowledge
Principles of Digital Signal Processing:
Sampling and Reconstruction
Digital Filters
DFT and FFT
Fast FFT-based Convolution
Sectral Analysis
Signal Generation
Real-time Signal Processing:
Interrupt and Polling
Block-based Signal Processing
Sampling and Reconstruction
Digital Filters
DFT and FFT
Fast FFT-based Convolution
Sectral Analysis
Signal Generation
Real-time Signal Processing:
Interrupt and Polling
Block-based Signal Processing
Skills
Apply fundamentals of digital signal processing:
Understanding of and ablilty to explain the fundamental principles of digital signal processing
Ability to compare and evaluate different digital filter types and different implementations
Implementation of real-time DSP:
Ability to explain the general problem of real-time DSP
Abilty to name aspects influencing the processing speed
Understanding of and ablilty to explain the fundamental methods of real-time digital signal processing
Understanding of and ablilty to explain the fundamental principles of digital signal processing
Ability to compare and evaluate different digital filter types and different implementations
Implementation of real-time DSP:
Ability to explain the general problem of real-time DSP
Abilty to name aspects influencing the processing speed
Understanding of and ablilty to explain the fundamental methods of real-time digital signal processing
Expenditure classroom teaching
| Type | Attendance (h/Wk.) |
|---|---|
| Lecture | 1 |
| Tutorial (voluntary) | 0 |
Special literature
keine/none
Special requirements
none
Accompanying material
Lecture slides
Example code snippets
Example code snippets
Separate exam
none
Learning goals
Skills
Implementation of fundamental methods and procedures for signal processing in Python/Matlab and on microprozessors.
Expenditure classroom teaching
| Type | Attendance (h/Wk.) |
|---|---|
| Practical training | 2 |
| Tutorial (voluntary) | 0 |
Special literature
keine/none
Special requirements
none
Accompanying material
Lab instructions with code skeletons
Separate exam
none
Learning goals
Skills
Implementation Python/Matlab:
Program, debug and optimize algorithm in Python Matlab.
Implementierung on microporocessor:
Port algorithm to target micorprocessor platform
Familiarity with development environment
Optimize algorithm for target platform
Solve complex tasks in team work:
Plan simple projects
Keep agreements and deadlines
Schedule and carry out reviews
Implementation of DSP algorithm on microporcessor platform:
Understand given methods for digital signal processing
Obtain required references for given methods
Translate mathematical methods to program code
Test, verify, and optimize program code
Presentation of results:
Presentation of project results
Program, debug and optimize algorithm in Python Matlab.
Implementierung on microporocessor:
Port algorithm to target micorprocessor platform
Familiarity with development environment
Optimize algorithm for target platform
Solve complex tasks in team work:
Plan simple projects
Keep agreements and deadlines
Schedule and carry out reviews
Implementation of DSP algorithm on microporcessor platform:
Understand given methods for digital signal processing
Obtain required references for given methods
Translate mathematical methods to program code
Test, verify, and optimize program code
Presentation of results:
Presentation of project results
Expenditure classroom teaching
| Type | Attendance (h/Wk.) |
|---|---|
| Project | 1 |
| Tutorial (voluntary) | 0 |
Special literature
keine/none
Special requirements
none
Accompanying material
Installed software on lab computers
Microprozessor boards with code skeletons for free develpoment environment
Microprozessor boards with code skeletons for free develpoment environment
Separate exam
none
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