Compressive sampling of EEG signals with finite rate of innovation

DOI10.1155/2010/183105zbMath1204.94056OpenAlexW2071966758WikidataQ59249982 ScholiaQ59249982MaRDI QIDQ623983

Kok-Kiong Poh, Pina Marziliano

Publication date: 8 February 2011

Published in: EURASIP Journal on Advances in Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2010/183105

Mathematics Subject Classification ID

Sampling theory in information and communication theory (94A20)

Related Items (2)

Sparse sampling: theory, methods and an application in neuroscience ⋮ Modifications of Prony's method for the recovery and sparse approximation with generalized exponential sums

Cites Work

• EEG signal compression based on classified signature and envelope vector sets
• Sampling signals with finite rate of innovation

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