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F07_SIG_en
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Course Signal Processing
Course
Meets requirements of following modules(MID)
Course Organization
Assessment
Course components
Lecture/Exercise
Lab
Responsible:
Prof. Dr. Rainer Bartz
Course
Meets requirements of following modules(MID)
in active programs
Ba TIN2012 SIG
Ba TIN2010 DSS
Course Organization
Version
created
20130620
VID
1
valid from
WS 2012/13
valid to
Course identifiers
Long name
Signal Processing
CID
F07_SIG
CEID (exam identifier)
Contact hours per week (SWS)
Lecture
2
Exercise (unsplit)
Exercise (split)
1
Lab
1
Project
Seminar
Tutorial(voluntary)
Total contact hours
Lecture
30
Exercise (unsplit)
Exercise (split)
15
Lab
15
Project
Seminar
Tutorial (voluntary)
Max. capacity
Exercise (unsplit)
Exercise (split)
40
Lab
10
Project
Seminar
Total effort (hours):
150
Instruction language
German, 70%
English, 30%
Study Level
undergraduate
Prerequisites
basic programming skills
sequences and series
trigonometric, exponential and logarithmic functions
polynomial division
limits, infinite series, partial fraction expansion
differential and integral calculus
Textbooks, Recommended Reading
Carlson, G. E.: Signal and Linear System Analysis, John Wiley & Sons, Inc.
Instructors
Prof. Dr. Rainer Bartz
Supporting Scientific Staff
tba
Transcipt Entry
Signal Processing
Assessment
Type
wE
written exam
Total effort [hours]
wE
10
Frequency:
23/year
Course components
Lecture/Exercise
Objectives
Contents
basic concepts (signal, system, characteristics)
signals
discrete time reference signals (impulse, step, ...)
Fourier transform of discretetime signals
ztransform of discretetime signals
systems; signal transmission
discretetime (DT) LTI sytems
difference equations and block diagrams
DT convolution
ztransform of a delay element
the ztransfer function
responses on reference signals
general system responses
polezero plot and stability
FIR and IIR systems
design of DT filter systems
canonical system structures: DF1, DF2
FIR and IIR filter systems; comparison
Acquired Skills
students acquire fundamental knowledge on theory and applications of discretetime signals and systems
they understand the behavior of typical systems
they can apply algorithms for convolution, Fourier, and ztransform, and implement them in software
they are able to design a system, to model a system, and to analyze it in time and frequency domain
they can apply system theory to realworld systems
Operational Competences
students can implement a discretetime system based on given requirements
Additional Component Assessment
Type
fPS
supervised/assisted problem solving
Contribution to course grade
fPS
not rated
Frequency:
1/year
Lab
Objectives
Contents
sampling input and output signals of a CT system
basic algorithms of signal processing
software implementation of a DT system from a requirements specification
Acquired Skills
students can use state of the art tools for system modelling, simulation, and implementation
they understand the relationship between CT and DT systems and can explain the most important effects
Operational Competences
students are able to solve problems in small teams
they can analyze measurement results and extract knowledge about the underlying system
they are able to model and simulate a realworld system
they can detect a wrong sample rate and adjust it
they are able to implement basic algorithms of digital signal processing
Additional Component Assessment
Type
fSC
23 lab experiments
Contribution to course grade
fSC
prerequisite for course exam
Frequency:
1/year
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TopicRevision: r3  11 Jan 2016,
GeneratedContent
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