6 papers
Unified Fourier transform on graphs sampled from stochastic block models
Mahya Ghandehari, Jeannette Janssen, Silo Murphy
Recently, an approach to graph signal processing based on graphons was proposed. Here we show how such a graphon-driven approach to the Fourier transform can be used on graphs samp…
On amenability constants of Fourier algebras: new bounds and new examples
Yemon Choi, Mahya Ghandehari
Let be a locally compact group. If is finite then the amenability constant of its Fourier algebra, denoted by , admits an explicit formula [Johnson, J…
Consistent sampling of Paley-Wiener functions on graphons
Hartmut Führ, Mahya Ghandehari
We study sampling methods for Paley-Wiener functions on graphons, thereby adapting and generalizing methods initially developed for graphs to the graphon setting. We then derive co…
On the restriction maps of the Fourier and Fourier-Stieltjes algebras over locally compact groupoids
Joseph DeGaetani, Mahya Ghandehari
The Fourier and Fourier-Stieltjes algebras over locally compact groupoids have been defined in a way that parallels their construction for groups. In this article, we extend the re…
Frames for signal processing on Cayley graphs
Kathryn Beck, Mahya Ghandehari, Skyler Hudson +1
The spectral decomposition of graph adjacency matrices is an essential ingredient in the design of graph signal processing (GSP) techniques. When the adjacency matrix has multi-dim…
Constructing non-AMNM weighted convolution algebras for every semilattice of infinite breadth
Yemon Choi, Mahya Ghandehari, Hung Le Pham
The AMNM property for commutative Banach algebras is a form of Ulam stability for multiplicative linear functionals. We show that on any semilattice of infinite breadth, one may co…