A rakeness-based design flow for Analog-to-Information conversion by Compressive Sensing

Valerio Cambareri; Mauro Mangia; Fabio Pareschi; Riccardo Rovatti; Gianluca Setti

doi:10.1109/ISCAS.2013.6572107

A rakeness-based design flow for Analog-to-Information conversion by Compressive Sensing

Valerio Cambareri, Mauro Mangia, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

27 Scopus citations

Abstract

Classical design of Analog-to-Information converters based on Compressive Sensing uses random projection matrices made of independent and identically distributed entries. Leveraging on previous work, we define a complete and extremely simple design flow that quantifies the statistical dependencies in projection matrices allowing the exploitation of non-uniformities in the distribution of the energy of the input signal. The energy-driven reconstruction concept and the effect of this design technique are justified and demonstrated by simulations reporting conspicuous savings in the number of measurements needed for signal reconstruction that approach 50%. © 2013 IEEE.

Original language	English (US)
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Pages	1360-1363
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2013.6572107
State	Published - Sep 9 2013
Externally published	Yes

Bibliographical note

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

Access to Document

10.1109/ISCAS.2013.6572107

Cite this

@inproceedings{1adaf17cffd248bea22ecd2d406557b4,

title = "A rakeness-based design flow for Analog-to-Information conversion by Compressive Sensing",

abstract = "Classical design of Analog-to-Information converters based on Compressive Sensing uses random projection matrices made of independent and identically distributed entries. Leveraging on previous work, we define a complete and extremely simple design flow that quantifies the statistical dependencies in projection matrices allowing the exploitation of non-uniformities in the distribution of the energy of the input signal. The energy-driven reconstruction concept and the effect of this design technique are justified and demonstrated by simulations reporting conspicuous savings in the number of measurements needed for signal reconstruction that approach 50%. {\textcopyright} 2013 IEEE.",

author = "Valerio Cambareri and Mauro Mangia and Fabio Pareschi and Riccardo Rovatti and Gianluca Setti",

note = "Generated from Scopus record by KAUST IRTS on 2023-02-15",

year = "2013",

month = sep,

day = "9",

doi = "10.1109/ISCAS.2013.6572107",

language = "English (US)",

isbn = "9781467357609",

pages = "1360--1363",

booktitle = "Proceedings - IEEE International Symposium on Circuits and Systems",

}

TY - GEN

T1 - A rakeness-based design flow for Analog-to-Information conversion by Compressive Sensing

AU - Cambareri, Valerio

AU - Mangia, Mauro

AU - Pareschi, Fabio

AU - Rovatti, Riccardo

AU - Setti, Gianluca

N1 - Generated from Scopus record by KAUST IRTS on 2023-02-15

PY - 2013/9/9

Y1 - 2013/9/9

N2 - Classical design of Analog-to-Information converters based on Compressive Sensing uses random projection matrices made of independent and identically distributed entries. Leveraging on previous work, we define a complete and extremely simple design flow that quantifies the statistical dependencies in projection matrices allowing the exploitation of non-uniformities in the distribution of the energy of the input signal. The energy-driven reconstruction concept and the effect of this design technique are justified and demonstrated by simulations reporting conspicuous savings in the number of measurements needed for signal reconstruction that approach 50%. © 2013 IEEE.

AB - Classical design of Analog-to-Information converters based on Compressive Sensing uses random projection matrices made of independent and identically distributed entries. Leveraging on previous work, we define a complete and extremely simple design flow that quantifies the statistical dependencies in projection matrices allowing the exploitation of non-uniformities in the distribution of the energy of the input signal. The energy-driven reconstruction concept and the effect of this design technique are justified and demonstrated by simulations reporting conspicuous savings in the number of measurements needed for signal reconstruction that approach 50%. © 2013 IEEE.

UR - http://ieeexplore.ieee.org/document/6572107/

UR - http://www.scopus.com/inward/record.url?scp=84883383158&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2013.6572107

DO - 10.1109/ISCAS.2013.6572107

M3 - Conference contribution

SN - 9781467357609

SP - 1360

EP - 1363

BT - Proceedings - IEEE International Symposium on Circuits and Systems

ER -

A rakeness-based design flow for Analog-to-Information conversion by Compressive Sensing

Abstract

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this