Compressed sensing exploits special signal features to extract its information content with a smaller amount of samples with respect to acquisition based on Nyquist theorem. While many theoretical results have proved the capabilities of this new paradigm, hardware implementations are still far from being practical. Here, we present a new architecture of analog to information converter that produces 1-bit compressive measurements. The performance of the architecture can be boosted if the signal to acquire features, beyond the classically required sparsity, also some sort of localization of its energy. The effectiveness of the architecture and of its enhancement is shown in the measurement of EEG, that presents a non-uniform spectral profile.

An Architecture for 1-Bit Localized Compressive Sensing with Applications to EEG / Javier Haboba; Mauro Mangia; Riccardo Rovatti; Gianluca Setti. - STAMPA. - (2011), pp. 324-327. (Intervento presentato al convegno IEEE Conference on Biomedical Circuits and Systems Conference tenutosi a Sand Diego (California) nel 10-12 November 2011) [10.1109/BioCAS.2011.6107746].

An Architecture for 1-Bit Localized Compressive Sensing with Applications to EEG

HABOBA, SALVADOR JAVIER;MANGIA, MAURO;ROVATTI, RICCARDO;
2011

Abstract

Compressed sensing exploits special signal features to extract its information content with a smaller amount of samples with respect to acquisition based on Nyquist theorem. While many theoretical results have proved the capabilities of this new paradigm, hardware implementations are still far from being practical. Here, we present a new architecture of analog to information converter that produces 1-bit compressive measurements. The performance of the architecture can be boosted if the signal to acquire features, beyond the classically required sparsity, also some sort of localization of its energy. The effectiveness of the architecture and of its enhancement is shown in the measurement of EEG, that presents a non-uniform spectral profile.
2011
Proceedings Biomedical Circuits and Systems Conference (BioCAS), 2011 IEEE
324
327
An Architecture for 1-Bit Localized Compressive Sensing with Applications to EEG / Javier Haboba; Mauro Mangia; Riccardo Rovatti; Gianluca Setti. - STAMPA. - (2011), pp. 324-327. (Intervento presentato al convegno IEEE Conference on Biomedical Circuits and Systems Conference tenutosi a Sand Diego (California) nel 10-12 November 2011) [10.1109/BioCAS.2011.6107746].
Javier Haboba; Mauro Mangia; Riccardo Rovatti; Gianluca Setti
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/109045
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