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Title
Compressed sensing for graph signals / by Ahmed Tawfik
AuthorTawfik, Ahmed
CensorGörtz, Norbert
Published2018
Description55 Blätter : Diagramme
Institutional NoteTechnische Universität Wien, Diplomarbeit, 2018
LanguageEnglish
Document typeThesis (Diplom)
Keywords (DE)Compressed Sensing / Graph Signals
Keywords (EN)Compressed Sensing / Graph Signals
URNurn:nbn:at:at-ubtuw:1-109851 Persistent Identifier (URN)
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 The work is publicly available
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Compressed sensing for graph signals [1.87 mb]
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Abstract (English)

In this thesis we are going to tackle the problem of estimating a sparse graph signal with an unknown frequency support set of known size K from a sampled noisy version. Not knowing the location of the non-zero Fourier coefficients and by taking a number M of samples larger than K will give us a compressed sensing problem. The Bayesian Approximate Message Passing (BAMP) algorithm is used to solve the compressed sensing problem and recover the original signal from few coefficients.

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