Graph filter designs and implementations

J. Liu

Research output: ThesisDissertation (TU Delft)

11 Downloads (Pure)

Abstract

The ability to model irregular data and the interactions between them have
extended the traditional signal processing tools to the graph domain. Under
these circumstances, the emergence of graph signal processing has offered a
brand new framework for dealing with complex data. In particular, the graph
Fourier transform (GFT) lets us analyze the spectral components of a graph signal in the graph frequency domain. Based on the GFT, graph filters provide useful tools to modify or extract spectral parts in terms of different objectives, e.g., using a low-pass graph filter to construct graph signals without noise. This thesis mainly focuses on designing and implementing graph filters. Similar to traditional signal processing, we investigate two types of graph filters: finite impulse response (FIR) and infinite impulse response (IIR) graph filters. Moreover, this thesis takes both undirected and directed graphs into account for the design methods and implementations.
Original languageEnglish
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Leus, G.J.T., Supervisor
Award date25 Jun 2021
Print ISBNs978-94-6423-321-6
DOIs
Publication statusPublished - 2021

Keywords

  • Graph signal processing
  • graph filters
  • adjacency
  • Laplacian
  • FIR
  • ARMA
  • linear system on graphs
  • graph filter implementation

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