| 
        
          
          
         
          |  Inhalt
              
                
                  | [ 536DASCDSPU19 ]                                         UE                                         (*)Digital Signal Processing |  
                  |  |  |  | Es ist eine neuere Version 2025W dieser LV im Curriculum Masterstudium Polymer Engineering and Science 2025W vorhanden. |  
                  |  |  
                  | (*)  Leider ist diese Information in Deutsch nicht verfügbar. |  
                  |  | 
                    
                      | Workload | Ausbildungslevel | Studienfachbereich | VerantwortlicheR | Semesterstunden | Anbietende Uni |  
                      | 1,5 ECTS | B3 - Bachelor 3. Jahr | Artificial Intelligence | Mario Huemer | 1 SSt | Johannes Kepler Universität Linz |  |  
                  |  |  
                  |  | 
                        
    					  
    					  
  						
                    
                      | Detailinformationen |  
                      | Quellcurriculum | Bachelorstudium Artificial Intelligence 2022W |  
                      | Ziele | (*)Students know and understand the basics of analog as well as discrete-time signals and systems qualitatively and mathematically and can apply them to fundamental problems. They are able to plot signals in time- and frequency domain,
explain the sampling theorem,
apply the convolution operation,
derive the spectrum of a signal numerically with the help of the DFT and the FFT,
describe the behavior of discrete-time LTI systems in time- and frequency domain, 
analyze and design digital FIR and IIR filters, and 
apply the correlation operation.
 Students know and understand the basics of adaptive filters, and the basics of time-frequency analysis.
 |  
                      | Lehrinhalte | (*) Basics of Analog Systems Theory
Discrete Time Signals Fundamentals
Discrete Time LTI Systems Fundamentals
Fourier Transform of Discrete Time Signals (DTFT)
Sampling and Reconstruction
Correlation
Spectral Analysis of Discrete Time Signals (DFT, FFT, Short Time Fourier Transformation, Applications)
z Transform
Digital Filters (FIR, IIR)
Vector Matrix Representations of Discrete Time Signals and LTI Systems
Adaptive Filters
 |  
                      | Beurteilungskriterien | (*)Homework to be uploaded and evaluated |  
                      | Lehrmethoden | (*) Demonstration of examples
Matlab examples
Homework
 |  
                      | Abhaltungssprache | Englisch |  
                      | Literatur | (*) Lecture Slides
Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing: Pearson New International Edition, Pearson Education Limited 2014.
 |  
                      | Lehrinhalte wechselnd? | Nein |  |  
                  |  |  
                  |  | 
                    
    				  
    				  
  					
                    
                      | Präsenzlehrveranstaltung |  
                        | Teilungsziffer | 35 |  
                      | Zuteilungsverfahren | Direktzuteilung |  |  |  |