Course Signal Processing with Matlab Microprocessor and DSP


Responsible: Prof.Dr.Elders-Boll

Course

Meets requirements of following modules(MID)

Course Organization

Version
created 2013-05-17
VID 2
valid from WS 2012/13
valid to
Course identifiers
Long name Signal Processing with Matlab Microprocessor and DSP
CID F07_SMMD
CEID (exam identifier)

Contact hours per week (SWS)
Lecture 1
Exercise (unsplit)
Exercise (split)
Lab
Project 2
Seminar
Tutorial(voluntary)
Total contact hours
Lecture 15
Exercise (unsplit)
Exercise (split)
Lab
Project 30
Seminar
Tutorial (voluntary)
Max. capacity
Exercise (unsplit)
Exercise (split) 40
Lab 18
Project 18
Seminar 40

Total effort (hours): 180

Instruction language

  • German,30%
  • English, 70%

Study Level

  • Undergraduate

Prerequisites

  • Basic programming skills
  • Basic knowledge of signals and systems
    • Sampling theorem
    • Digital filters
    • Fourier transform

Textbooks, Recommended Reading

  • Welch, Wright, Morrow: Real-Time Digital Signal Processing (CRC Press)

Instructors

  • Prof.Dr.Elders-Boll
  • Prof. Dr.-Ing. Uwe Dettmar
  • Prof. Dr.-Ing. Christoph Pörschmann

Supporting Scientific Staff

  • Dipl.-Ing. Martin Seckler

Transcipt Entry

Signal Processing with Matlab, Microprocessor, and DSP

Assessment

Type
oR presentation of the team project results (40%)
wR Written report of the team projects results (40%)

Total effort [hours]
oR 30

Frequency: 1/year


Course components

Lecture/Exercise

Objectives

Contents
  • Principles of Digital Signal Processing
    • Sampling and Reconstruction
    • Digital Filters
      • FIR Filters
      • IIR Filters
    • DFT and FFT
    • FFT-Implementation of FIR Filters
      • Overlap-Save
      • Overlap-Add
    • Spectral Analysis
      • Window Functions
    • Signal Generation
  • Real-Time Signal Processing
    • Interrupt und Polling
    • Frame-Based DSP

Acquired Skills
  • understand and explain the basic principles of digital signal processing
  • ability to compare and evaluate different filter types and filter implementations
  • explain the general challanges of real-time DSP
  • name parameters that influence the real-time capability of DSP algorithms
  • understand and ability to explain the basic methods for real-time DSP

Additional Component Assessment

Type
fAP 1-2 tests

Contribution to course grade
fAP 1-2 tests (20%)

Frequency: 1/year

Seminar/Projekt

Objectives

Acquired Skills
  • Implementation of DSP algorithms in Matlab
    • Implementation as Matlab code
    • Debugging and code optimization
    • Ability to apply Matlab tools
      • Filter Designer
  • Implementation of DSP algorithms on microprocessors or DSPs
    • Implementation as c-code on target processor
    • Ability to use software development tools
      • Debugging and code optimization
    • Knowledge of properties of development board and processor
    • Code optimization on target hardware

Operational Competences
  • Manage complex tasks as a team
  • Implement DSP algorithms on target hardware
    • Understand a given DSP task and the method for solving it
    • Implement a DSP algorithm given in mathematical notation in software
    • Verify program code
    • Optimize program code
  • Presentation of results
    • Presentation of the team project results (in English)

Additional Component Assessment

Type
fTP team project
fIN 2-3 supervised team meetings with lecturer

Contribution to course grade
fTP prerequisite for admission to oral presentation
fIN prerequisite for admission to oral presentation

Frequency: 1/year

Topic-Revision: r4 - 11 Jan 2016, GeneratedContent
 
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