Compressed Sensing of ΔΣ Streams

Sergio Callegari, Mauro Mangia, Riccardo Rovatti, Gianluca Setti

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Compressed sensing (CS) is often applied at the digital level. We consider the case where CS follows a Δ Σ data converter and we show that CS can be practiced directly on the Δ Σ stream. In the proposed scheme, an appropriate sensing matrix incorporates the ability to get rid of the quantization noise from the Δ Σ modulator. We also show that a suitable sparsity basis enables the CS information recovery to be practiced directly at the Nyquist rate and that decimation, which is typically inherent in Δ Σ data acquisition, is not needed. Furthermore, the low depth of Δ Σ streams allows CS measures to be taken without multipliers, streamlining arithmetic blocks. A test case based on electrocardiograms is used to validate the approach.
Original languageEnglish (US)
Title of host publication2019 26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Print)9781728109961
StatePublished - Nov 1 2019
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15


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