Investigation of Joint Sparsity models for Compressed Sensing

Tutor: Tobias Schnier
Type of Thesis: Studienarbeit (Dipl.)
date of end: 01/2016
Student: Jörg Holzapfel
Status: finished

In this topic, the multiple measurement part of Compressed Sensing is investigated.

Main questions:

Is there a inherit structure in my measurements (like adjacent sensor nodes) that can be exploited?

Are there different types of models that are common?


Imagine you have several temperature sensors in your room. Then its most likely that they measurement temperature is similar on all sensors, because its determined by global variables.

But locally there can be disturbances that change the individual sensors. Can this given global/local model be used to need less measurements overall?

Work to do:

Literature search of already known joint sparsity models

Researching new joint sparsity models and presenting apllications for it

MATLAB-programming of synthetically designed problems to evaluate the efficiency of the models

Expertise needed:

Basic mathematical background is needed

Last change on 04.01.2016 by
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