Finite Rate of Innovation Representation of Real Neuro Data

Betreuer: Tobias Schnier
Art der Arbeit: Masterarbeit (MSc)
Arbeit beendet: 10/2016
Bearbeiter: Maik Röper
Status: abgeschlossen

In this project possible FRI-dictionaries for real neuro data are evaluated and new dicitionaries proposed.

Main questions:

Are polynomial splines sufficient for the representation of Neuro Data?

Do exponential splines lead to a better representaion?


Through wireless implants neuro data is transmitted out of the brain via Finite Rate of Innovation (FRI) algorithms. To reconstruct them properly a well designed dictionary is needed that can represent the real neuro data in a practical way.

Work to do:

Literature search of common FRI methods

Test found dictionaries on real neuro data

MATLAB-programming of found FRI algorithms and testing them on real neuro data

Expertise needed

FRI knowledge is helpful but not a requirement

Basic mathematical background is needed

Basis MATLAB knowledge is needed

Zuletzt aktualisiert am 26.01.2017 von
AIT ieee GOC tzi ith Fachbereich 1
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