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Compressed Sensing of Generative Sparse-Latent (GSL) Signals
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering. Digital Futures, Stockholm, Sweden.ORCID iD: 0000-0003-0166-1356
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering. Digital Futures, Stockholm, Sweden.ORCID iD: 0000-0001-6612-6923
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering. Digital Futures, Stockholm, Sweden.ORCID iD: 0000-0003-2638-6047
2023 (English)In: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings, European Signal Processing Conference, EUSIPCO , 2023, p. 1918-1922Conference paper, Published paper (Refereed)
Abstract [en]

We consider reconstruction of an ambient signal in a compressed sensing (CS) setup where the ambient signal has a neural network based generative model. The generative model has a sparse-latent input and we refer to the generated ambient signal as generative sparse-latent signal (GSL). The proposed sparsity inducing reconstruction algorithm is inherently non-convex, and we show that a gradient based search provides a good reconstruction performance. We evaluate our proposed algorithm using simulated data.

Place, publisher, year, edition, pages
European Signal Processing Conference, EUSIPCO , 2023. p. 1918-1922
Keywords [en]
Compressed sensing, generative models, inverse problems
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-340801DOI: 10.23919/EUSIPCO58844.2023.10289923Scopus ID: 2-s2.0-85178384307OAI: oai:DiVA.org:kth-340801DiVA, id: diva2:1819628
Conference
31st European Signal Processing Conference, EUSIPCO 2023, Helsinki, Finland, Sep 4 2023 - Sep 8 2023
Note

Part of ISBN 9789464593600

QC 20231214

Available from: 2023-12-14 Created: 2023-12-14 Last updated: 2023-12-14Bibliographically approved

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Honore, AntoineGhosh, AnubhabChatterjee, Saikat

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  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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Output format
  • html
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  • asciidoc
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