Course Manual DSS

Discrete Signals and Systems

PDF Course Catalog Deutsche Version: DSS

Version: 2 | Last Change: 11.09.2019 11:39 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben

General information

Long name	Discrete Signals and Systems
Approving CModule	DSS_BaET
Responsible	Prof. Dr. Harald Elders-Boll Professor Fakultät IME
Valid from	summer semester 2022
Level	Bachelor
Semester in the year	summer semester
Duration	Semester
Hours in self-study	60
ECTS	5
Professors	Prof. Dr. Harald Elders-Boll Professor Fakultät IME
Requirements	Knowledge of the following mathematical subjects: Trigonometric functions, exponential function, logarithm, complex calculus, integral and differential calculus, series expansion, geometric series, partial fraction expansion. Knowledge of the following physical subjects: Work, power and energy.
Language	German
Separate final exam	Yes

Literature

Jens Rainer Ohm und Hans Dieter Lüke, Signalübertragung, Springer, 2014

Martin Meyer, Signalverarbeitung, Springer Vieweg, 2014

Martin Werner, Signale und Systeme, Springer Vieweg, 2008

Bernd Girot u.a., Einführung in die Systemtheorie, Springer Vieweg, 2007

Final exam

Details	During the exam students shall demonstrate by solving problems dealing with the methods and algorithms for the analysis and the processing of discrete-time signals and systems, such as discret convolution, DTFT, z-transform and DFT, that they are able to apply the fundamental terms, concepts and techniques of discrete signals and systems to determine and describe the propoerties of signals and sytems in the time and frequency domain, to digitize and analyse analog signals and process them with basic discrete-time systems.
Minimum standard	At least 24 of the 50 points that can be gained in total in the final exam and the two midterm tests during the semester. In the final exam 40 points can be gained in total, in the two midterm test 5 points can be gained each yielding 10 points in total for the two tests.
Exam Type	EN Klausur

Goal type	Description
Knowledge	Basic Concepts: Classification of signals and systems, stability, causality LSI Systems: discrete-time convolution, impulse response, stability, causality Sampling: sampled vs. discrete time signals, sampling theorem, aliasing DTFT: derivation, properties, calculation of the DTFT, frequency response z-Transform: derivation, properties, calculation of the inverse z-transform, system function, stability, block diagrams DFT: derivation, properties, leakage effect Basics of filter design: principles of FIR and IIR filter design, properties and comparison of FIR and IIR filters
Skills	Assessment of the stability of LSI systems Calculation of the DTFT and the z-transform and the corresponding inverse transforms Implementation of FIR systems by programming of the discrete-time convolution Implementation of basic IIR Systems Assessment of the characteristics of LSI filters

Basic Concepts: Classification of signals and systems, stability, causality
LSI Systems: discrete-time convolution, impulse response, stability, causality
Sampling: sampled vs. discrete time signals, sampling theorem, aliasing
DTFT: derivation, properties, calculation of the DTFT, frequency response
z-Transform: derivation, properties, calculation of the inverse z-transform, system function, stability, block diagrams
DFT: derivation, properties, leakage effect
Basics of filter design: principles of FIR and IIR filter design, properties and comparison of FIR and IIR filters

Skills

Assessment of the stability of LSI systems
Calculation of the DTFT and the z-transform and the corresponding inverse transforms
Implementation of FIR systems by programming of the discrete-time convolution
Implementation of basic IIR Systems
Assessment of the characteristics of LSI filters

Expenditure classroom teaching

Type	Attendance (h/Wk.)
Lecture	2
Exercises (whole course)	2
Exercises (shared course)	0
Tutorial (voluntary)	0

Special requirements

none

Accompanying material	Lecture slides as PDF documents Tutorial problems with solutions Old exams with solutions
Separate exam	Yes

Separate exam

Exam Type	EN Übungsaufgabe mit fachlich / methodisch eingeschränktem Fokus unter Klausurbedingungen lösen
Details	Two midterm tests with excercises dealing with the subjects from the lecture/tutorial that were covered up to that point, suich the by passing the midterm tests students demonstrate that they have the required skills to sucessfully participate in the corresponding labs.
Minimum standard	Two out of five points that can be scored in total per test.

Practical training

Learning goals

Goal type	Description
Skills	Two iPython-based labs on digital soignal processing of acoustical signals to apply the methods from the lecture tutorial to practical problems: 1. Discrete-time signals and systems in the time domain: Programming of the discrete-time convolution to implement FIR filters Programming of basic recursive (IIR) filters Assessment of the filter characteristics by hearing acoustical signals 2. Discrete-time signals and systems in the frequency domain: Analysis of basic FIR and IIR filters in the frequency domain using the DTFTR and the z-transform from Scipy Comparison of the auditory impression and the frequency response

Goal type

Description

Skills

Two iPython-based labs on digital soignal processing of acoustical signals to apply the methods from the lecture tutorial to practical problems:
1. Discrete-time signals and systems in the time domain:
Programming of the discrete-time convolution to implement FIR filters
Programming of basic recursive (IIR) filters
Assessment of the filter characteristics by hearing acoustical signals
2. Discrete-time signals and systems in the frequency domain:
Analysis of basic FIR and IIR filters in the frequency domain using the DTFTR and the z-transform from Scipy
Comparison of the auditory impression and the frequency response

Expenditure classroom teaching

Type	Attendance (h/Wk.)
Practical training	1
Tutorial (voluntary)	0

Special requirements

none

Accompanying material	Lab instructions as iPython notebooks.
Separate exam	Yes

Separate exam

Exam Type	EN praxisnahes Szenario bearbeiten (z.B. im Praktikum)
Details	Sucessful solution of the lab problems in small groups consisting of two students, in general. The corresponding midterm test from the lecture/tutorial needs to be passed as a prerequisite for participation in the lab.
Minimum standard	Successful participation of all labs. Per lab the substantial parts have to accomplished individually from each group. To pass the corresponding midterm test 2 out of 5 points have to be gained.