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CATEGORIES:Analysis seminar
SUMMARY:Sparse Approximation of Similar Signals - Laura R
ebollo-Neira\, Aston University
DTSTART:20221128T150000Z
DTEND:20221128T160000Z
UID:TALK4991AT
URL:/talk/index/4991
DESCRIPTION:A signal is any carrier of information that we rep
resent as an element of an inner product space. In
this talk we assume that the signals of interests
are well approximated in a significantly lower di
mension subspace. The aim is to look for a common
subspace suitable for approximating a set of sign
als of similar features. It is assumed that `simil
arity' in this context implies the existence of a
common basis spanning the sought subspace. A gree
dy selection process is introduced for finding the
common basis in a stepwise optimal manner. The se
lection is carried out by choosing elements from a
large redundant set called a `dictionary'. The si
multaneous approximation of a set of signals in th
e subspace is achieved by stepwise construction of
the dual basis. The sparser approximation of ind
ividual signals in the set is further considered t
hrough dedicated updating of the dual basis\, to p
roduce orthogonal projections onto subspaces of di
fferent dimension. The approach is illustrated us
ing wavelets dictionaries for the approximation of
Electrocardiograms (ECG signals). The results are
shown to be of practical relevance when applied t
o compression of ECG records.
LOCATION:WATN-LT C (G24)
CONTACT:Yuzhao Wang
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