Graph Fourier Transform for Samples of Structured Graphons (23rit007)

Organizers

Mahya Ghandehari (University of Delaware)

Jeannette Janssen (Dalhousie University)

Description

The Banff International Research Station will host the "Graph Fourier Transform for Samples of Structured Graphons" workshop in Banff from November 5 to November 12, 2023.


The proliferation of networked data in the past few decades has been unprecedented. In this type of data, numerical measurements are attached to the nodes of a network, and for successful analysis of the data, the underlying network structure should be taken into account. Over the past two decades, significant progress has been made to generalize classical signal processing tools to analyze and process signals defined on networks. This topic attracted the attention of many data scientists (in mathematics and engineering), and turned into the fast-growing and vibrant field of Graph Signal Processing.


One of the most fundamental concepts in classical signal processing is the Fourier transform. This concept has been generalized to graph signals, but processing of a graph signal rigidly depends on the underlying network; this is a major drawback, as the underlying graph of a signal may sustain minor variations due to error or the natural evolution of the network. In this RIT, we plan to develop techniques for designing instance-independent graph signal processing methods.


The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).