Conferencia Graph Signal Processing: Distributed Graph Filters

Graph signal processing extends the field of classical
signal processing to data with an irregular structure, which
can be characterized by means of a graph. Such data
appears for instance in sensor, social, traffic, and brain
networks, to name a few. One of the cornerstones of the field
of graph signal processing are graph filters, direct analogues
of time-domain filters, but intended for signals defined on
In this talk, we first introduce the frequency domain related
to a graph. This gives rise to a so-called graph Fourier
transform, which allows us to define graph filters. We give an
overview of the graph filtering problem and specify a number
of interesting applications, such as denoising, interpolating,
analyzing and classifying signals over a graph. Further, we
look at the family of finite impulse response (FIR) and infinite
impulse response (IIR) graph filters and show how they can
be implemented in a distributed manner.


Feb 19 2019


6:30 PM - 8:00 PM

Próximos eventos

¡No hay eventos!


Idioma del sitio

English English Español Español

Deja una respuesta

Tu dirección de correo electrónico no será publicada. Los campos obligatorios están marcados con *