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SUMMARY:EE Distinguished Lecturer Seminar: Topological Signal Processing
DTSTART:20190606T160000
DTEND:20190606T170000
DTSTAMP:20260528T031200Z
UID:0fe178d979c3d7fea6029accbf7c415a77cac8135ed2f9fdd678904e
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Sergio Barbarossa\, Sapienza University\, Rome\nAbstract
 : The goal of this talk is to present the basic tools for the representati
 on and processing of signals defined over a topological space\, i.e. a col
 lection of points only characterized by a set of neighborhood relations. M
 otivating applications are all signals defined over a non-metric space\, l
 ike gene regulatory networks\, brain networks\, social networks\, etc. The
  recent field of graph signal processing (GSP) is a particular case of top
 ological signal processing (TSP)\, referring to the situation where only p
 airwise relations among data are taken into account and then focusing only
  on signals defined over the vertices of a graph. Generalizing GSP\, our g
 oal is to incorporate multiway relations of various order by representing 
 signals over simplicial complexes\, to exploit their rich algebraic struct
 ure. After recalling the basic principles of algebraic topology\, we intro
 duce methods to build dictionaries capturing the metric-free structure of 
 the signal domain and leading to informative representations of signals de
 fined over sets of increasing order\, e.g.\, vertices\, edges\, etc. The i
 dentification of these dictionaries forms the basis of a spectral simplici
 al complex theory\, from which we establish an uncertainty principle and p
 resent its relation with sampling theory. After having introduced the anal
 ysis tools\, we consider the synthesis problem\, suggesting methods to inf
 er the structure of the simplicial complex from data. We conclude the talk
  presenting some interesting applications to real data and highlight possi
 ble future developments.\n\nBio: Sergio Barbarossa is a Full Professor at 
 Sapienza University of Rome. He has held several visiting positions at the
  Environmental Research Institute of Michigan (’88)\, Univ. of Virginia 
 (’95\, ‘97)\, Univ. of Minnesota (’99). He received the 2010 Technic
 al Achievements Award from the European Association for Signal Processing 
 (EURASIP) society for his contributions on radar\, communication and netwo
 rks and won the IEEE Best Paper Awards from the IEEE Signal Processing Soc
 iety for the years 2000 and 2014. He is an IEEE Fellow\, a EURASIP Fellow 
 and served as an IEEE Distinguished Lecturer. He has been the scientific c
 oordinator of several European projects on wireless sensor networks\, smal
 l cell networks\, and distributed mobile cloud computing. He is currently 
 managing the H2020 EU/Japan project 5G-MiEdge\, merging millimeter wave an
 d edge cloud technologies for 5G networks. He is involved in the H2020 pro
 ject 5G-Conni\, for the development of 5G private networks for Industry 4.
 0. His research interests include signal processing algorithms over topolo
 gical spaces\, topological methods for machine learning\, 5G networks and 
 mobile edge computing.
LOCATION:ELA 2 https://plan.epfl.ch/?room==ELA%202
STATUS:CONFIRMED
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