Graph filter designs and implementations

The ability to model irregular data and the interactions between them have<br/>extended the traditional signal processing tools to the graph domain. Under<br/>these circumstances, the emergence of graph signal processing has offered a<br/>brand new framework for dealing with complex data. In particular, the graph<br/>Fourier transform (GFT) lets...

Graph-time signal processing: Filtering and sampling strategies

The necessity to process signals living in non-Euclidean domains, such as signals defined on the top of a graph, has led to the extension of signal processing techniques to the graph setting. Among different approaches, graph signal processing distinguishes itself by providing a Fourier analysis of these signals. Analogously to the Fourier...

Distributed Graph Filters

We have recently seen a surge of research focusing on the processing of graph data. The emerging field of signal processing on graphs focuses on the extension of classical discrete signal processing techniques to the graph setting. Arguably, the greatest breakthrough of the field has been the extension of the Fourier transform from time signals...