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.
Compressed Sensing of ΔΣ Streams / Callegari, S.; Mangia, M.; Rovatti, R.; Setti, G.. - STAMPA. - (2019), pp. 835-838. (Intervento presentato al convegno IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019 tenutosi a ita nel 2019) [10.1109/ICECS46596.2019.8964730].
Compressed Sensing of ΔΣ Streams
Setti G.
2019
Abstract
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.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2834906