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SUMMARY:EE Distinguished Lecturer Seminar: Topological Signal Processing
DTSTART;VALUE=DATE-TIME:20190606T160000
DTEND;VALUE=DATE-TIME:20190606T170000
UID:0fe178d979c3d7fea6029accbf7c415a77cac8135ed2f9fdd678904e
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Sergio Barbarossa\, Sapienza University\, Rome\n**
Abstract**: The goal of this talk is to present the basic tools for
the representation and processing of signals defined over a topological s
pace\, i.e. a collection of points only characterized by a set of neighbor
hood relations. Motivating applications are all signals defined over a non
-metric space\, like gene regulatory networks\, brain networks\, social ne
tworks\, etc. The recent field of graph signal processing (GSP) is a parti
cular case of topological signal processing (TSP)\, referring to the situa
tion where only pairwise relations among data are taken into account and t
hen focusing only on signals defined over the vertices of a graph. General
izing GSP\, our goal is to incorporate multiway relations of various order
by representing signals over simplicial complexes\, to exploit their rich
algebraic structure. After recalling the basic principles of algebraic to
pology\, we introduce methods to build dictionaries capturing the metric-f
ree structure of the signal domain and leading to informative representati
ons of signals defined over sets of increasing order\, e.g.\, vertices\, e
dges\, etc. The identification of these dictionaries forms the basis of a
spectral simplicial complex theory\, from which we establish an uncertaint
y principle and present its relation with sampling theory. After having in
troduced the analysis tools\, we consider the synthesis problem\, suggesti
ng methods to infer the structure of the simplicial complex from data. We
conclude the talk presenting some interesting applications to real data an
d highlight possible future developments.

\n

\n**Bio: **Sergio Barbarossa is a Full Professor at Sapienza University of Rome. He
has held several visiting positions at the Environmental Research Institut
e of Michigan (’88)\, Univ. of Virginia (’95\, ‘97)\, Univ. of Minne
sota (’99). He received the 2010 Technical Achievements Award from the E
uropean Association for Signal Processing (EURASIP) society for his contri
butions on radar\, communication and networks and won the IEEE Best Paper
Awards from the IEEE Signal Processing Society for the years 2000 and 2014
. He is an IEEE Fellow\, a EURASIP Fellow and served as an IEEE Distinguis
hed Lecturer. He has been the scientific coordinator of several European p
rojects on wireless sensor networks\, small cell networks\, and distribute
d mobile cloud computing. He is currently managing the H2020 EU/Japan proj
ect 5G-MiEdge\, merging millimeter wave and edge cloud technologies for 5G
networks. He is involved in the H2020 project 5G-Conni\, for the developm
ent of 5G private networks for Industry 4.0. His research interests includ
e signal processing algorithms over topological spaces\, topological metho
ds for machine learning\, 5G networks and mobile edge computing.
LOCATION:ELA 2 https://plan.epfl.ch/?room=ELA2
STATUS:CONFIRMED
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