Leibniz Universität Hannover Fakultät Fakultät für Elektrotechnik und Informatik
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Institut für Kommunikationstechnik
 
Institut für Kommunikationstechnik Studium Lehrveranstaltungen

Graph Signal Processing

The goal of this lecture is to convey the following skills:

  • understand the fundamentals of Graph Signal (GS) representation and GS processing based on spectral graph theory
  • obtain an overview and technical depth of some methods for graph filtering and sampling
  • apply GSP methods to a range of areas including the analysis of distributed sensor networks and point clouds

This is a theory lecture with applications from volumetric multimedia processing and machine learning. The lecture is given in English.

Einleitungsbild Einleitungsbild Einleitungsbild

Contents

  • Short introduction to graph signals and node domain processing
  • Node domain graph filters
  • Graph Fourier Transform, Filtering 
  • Application of GFT to common operators
  • Graph Spectra
  • Graph Signal models, node domain sampling, frequency domain sampling, Conditions for reconstruction
  • Robust Graph spectral sampling
  • Applications of GSP to domains including transportation networks, sensor networks, point clouds, and learning with Graph Signals

Dates

Summer term

Lecture

  • Mo, 10:00 - 11:30, Room 3403 - A141
  • Start Lecture: 13.04.2026

Exercise

  • Mo 14:30 - 16:00, Room 3403 - A141

Materials

Materials will be distributed via Stud.IP

Exam

Written Exam (90 min)

Prüfungs- und Vorlesungsanmeldung

Ihr Dozent

Amr Rizk Amr Rizk
Prof. Dr. Amr Rizk
Professorinnen und Professoren
Telefon
+49 511 762 14832
Fax
+49 511 762 3030
E-Mail
amr.rizkikt.uni-hannover.de
Adresse
Appelstraße 9a
30167 Hannover
Gebäude
3408
Raum
1421
Amr Rizk Amr Rizk
Prof. Dr. Amr Rizk
Professorinnen und Professoren
Telefon
+49 511 762 14832
Fax
+49 511 762 3030
E-Mail
amr.rizkikt.uni-hannover.de
Adresse
Appelstraße 9a
30167 Hannover
Gebäude
3408
Raum
1421

Letzte Änderung: 07.04.26 Druckversion

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