Leibniz Universität Hannover Faculty Faculty of Electrical Engineering and Computer Science
Deutsch Contact Deutsch
Institute of Communications Technology
 
Institute of Communications Technology Studies Lectures

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.

Hero Image Hero Image Hero Image

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, 10:30 - 12:00, Room 3403 - A141
  • Start Lecture: 13.04.2026

Exercise

  • Mo 14:30 - 16:00, Room 3403 -  A141
  • Start Exercise: 13.04.2026

Materials

Materials will be distributed via Stud.IP

Exam

Written Exam (120 min)

Prüfungs- und Vorlesungsanmeldung

Ihr Dozent

Amr Rizk Amr Rizk
Prof. Dr. Amr Rizk
Professors
Phone
+49 511 762 14832
Fax
+49 511 762 3030
Email
amr.rizkikt.uni-hannover.de
Address
Appelstraße 9a
30167 Hannover
Building
3408
Room
1421
Amr Rizk Amr Rizk
Prof. Dr. Amr Rizk
Professors
Phone
+49 511 762 14832
Fax
+49 511 762 3030
Email
amr.rizkikt.uni-hannover.de
Address
Appelstraße 9a
30167 Hannover
Building
3408
Room
1421

Last Change: 06.01.26 Print

Contact us
Contact