Finite Rate of Innovation (FRI) - Reconstruction of Splines

Betreuer: Tobias Schnier
Art der Arbeit: Masterarbeit (MSc)
Arbeit beendet: 02/2017
Bearbeiter: Zhang Dacheng
Status: abgeschlossen
ANT-Signatur:
Kurzfassung:

In this thesis, the topic Finite Rate of Innovation is analyzed.


Main Questions:

-Are the requirements of FRI fulfilled for splines?

-How can splines be reconstructed with the FRI approach?

-Can the FRI approach be generalized to reconstruct several splines, that share some common attributes (e.g. knots at the same time instances)? (only for master thesis)

Applications

The lossless compression of Neuro signals is an open research topic. As Neuro signals fulfill the FRI requirements and splines are a good approximation with lower FRI, splines are a good candidate for this task.


Work to Do

-Literature research of given papers on FRI

-Evaluation of the requirements towards splines

-Implementation of spline reconstruction algorithms


Expertise needed

Intermediate math and MATLAB-skills

Zuletzt aktualisiert am 20.06.2017 von
AIT ieee GOC tzi ith Fachbereich 1
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