Maximum entropy hadamard sensing of sparse and localized signals

Valerio Cambareri, Riccardo Rovatti, Gianluca Setti

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

4 Scopus citations


The quest for optimal sensing matrices is crucial in the design of efficient Compressed Sensing architectures. In this paper we propose a maximum entropy criterion for the design of optimal Hadamard sensing matrices (and similar deterministic ensembles) when the signal being acquired is sparse and non-white. Since the resulting design strategy entails a combinatorial step, we devise a fast evolutionary algorithm to find sensing matrices that yield high-entropy measurements. Experimental results exploiting this strategy show quality gains when performing the recovery of optimally sensed small images and electrocardiographic signals. © 2014 IEEE.
Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Print)9781479928927
StatePublished - Jan 1 2014
Externally publishedYes

Bibliographical note

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


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