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Keynote Lectures

Extending Narrowband Descriptions and Optimal Solutions to Broadband Sensor Arrays
Stephan Weiss, University of Strathclyde, United Kingdom

The Use of Internet of Things for Smart Cities
Jaime Lloret Mauri, Universidad Politecnica de Valencia, Spain

 

Extending Narrowband Descriptions and Optimal Solutions to Broadband Sensor Arrays

Stephan Weiss
University of Strathclyde
United Kingdom
 

Brief Bio

I obtained the Dipl.-Ing.~degree from the University of Erlangen-Nuernberg, Erlangen, Germany, in 1995, and a Ph.D.~degree from the University of Strathclyde, Glasgow, Scotland, in 1998, both in electronic and electrical engineering. Following previous academic appointments at both the Universities of Strathclyde and Southampton, I am professor and head of the Centre for Signal and Image Processing (CeSIP) at Strathclyde. I previously have had visiting roles at the University of Southern California and Samara State Aerospace University, and am a guest professor at Alpen-Adria University in Klagenfurt, Austria.
My research interests lie in adaptive, multirate, and array signal processing with applications in communications, audio, and biomedical signal processing, where I published more than 280 technical papers.  For my work in biomedical signal processing, I was a co-recipient of the 2001 research award of the German society on hearing aids, and was a co-recipient of several best paper awards.
I am a member of EURASIP and a senior member of the IEEE. Previously, I was the technical co-chair an co-organiser for EUSIPCO 2009 and general chair of IEEE ISPLC 2014, both held in Glasgow, and am part of the organising committee for ICASSP 2019. I am an associate editor for Elsevier Digital Signal Processing, and previously served on the editorial boards of Elsevier Signal Processing and IEEE Transactions on Mobile Computing.


Abstract
In this presentation I will motivate the description of broadband sensor array problems by polynomial matrices, directly extending notation that is familiar from the characterisation of narrowband problems. To admit optimal solutions relies on extending the utility of the eigen- and singular value decompositions, by finding decompositions of such polynomial matrices. Particularly the factorisation of parahermitian polynomial matrices --- including space-time covariance matrices that model the second order statistics of broadband sensor array data --- is important. I will show recent findings on the existence and uniqueness of the eigenvalue decomposition of such parahermitian polynomial matrices, demonstrate some algorithms that implement such factorisations, and highlight key applications where such techniques can provide advantages over state-of-the-art solutions.



 

 

The Use of Internet of Things for Smart Cities

Jaime Lloret Mauri
Universidad Politecnica de Valencia
Spain
 

Brief Bio
Prof. Jaime Lloret received his B.Sc.+M.Sc. in Physics in 1997, his B.Sc.+M.Sc. in electronic Engineering in 2003 and his Ph.D. in telecommunication engineering (Dr. Ing.) in 2006. He is a Cisco Certified Network Professional Instructor. He worked as a network designer and administrator in several enterprises. He is currently Associate Professor in the Polytechnic University of Valencia. He is the Chair of the Integrated Management Coastal Research Institute (IGIC) and he is the head of the "Active and collaborative techniques and use of technologic resources in the education (EITACURTE)" Innovation Group. He is the director of the University Diploma “Redes y Comunicaciones de Ordenadores” and he has been the director of the University Master "Digital Post Production" for the term 2012-2016.


Abstract
Recent advances in new technologies jointly with the appearance of low cost sensors with computing and communication capacities have made possible to implement new systems to improve citizens daylife. Internet of Things allows monotiring from everywhere at any time. This speech will review recent developments of sensors and internet of things to gather data from urban environments and which network protocols, algorithms and architectures have been designed and developed to provide the most updated data. The knowledge acquired by these sensors can be tackled in order to improve the electric consumption, the water wastage and even any type of lakes in gas, electricity or water. Big data and artificial intelligence techniques can be used to optimize the resources of the cities and improve their performance. The talk will explain several examples and provide real implementations.



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