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SUMMARY:Analysis of time series observed on networks - Nunes\, M (Lancaste
 r University)
DTSTART:20140115T093000Z
DTEND:20140115T100000Z
UID:TALK49924@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:In this talk we consider analysis problems for time series tha
 t are observed at nodes of a large network structure. Such problems common
 ly appear in a vast array of fields\, such as environmental time series ob
 served at different spatial locations or measurements from computer system
  monitoring. The time series observed on the network might exhibit differe
 nt characteristics such as nonstationary behaviour or strong correlation\,
  and the nodal series evolve according to the inherent spatial structure.\
 n\nThe new methodology we develop hinges on reducing dimensionality of the
  original data through a change of basis. The basis we propose is a second
  generation wavelet basis which operates on spatial structures. As such\, 
 the (large) observed data is replaced by data over a reduced network topol
 ogy. We give examples of the potential of this dimension reduction method 
 for time series analysis tasks. This is joint work with Marina Knight (Uni
 versity of York) and Guy Nason (University of Bristol).\n
LOCATION:Seminar Room 1\, Newton Institute
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