Course Signal Processing with Matlab Microprocessor and DSP

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Responsible: Prof.Dr.Elders-Boll

Course

Meets requirements of following modules(MID)

• in active programs
  • Ba ET2012 SMMD
  • Ba ET2010 SMMD

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

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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