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DETECTION OF ROW-SPARSE MATRICES WITH ROW-STRUCTURE CONSTRAINTS

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Citation Author(s):
David Gregoratti
David Gregoratti, Carlos Buelga, Xavier Mestre
Submitted by:
David Gregoratti
Last updated:
9 May 2019 - 5:14am
Document Type:
Poster
Document Year:
2019
Event:
ICASSP 2019
Presenters:
Xavier Mestre
Paper Code:
3114
Categories:
Sampling and Reconstruction
 

An underdetermined multi-measurement vector linear regression problem is considered where the parameter matrix is row-sparse and where an additional constraint fixes the number of nonzero elements in the active rows. Even if this additional constraint offers side structure information that could be exploited to improve the estimation accuracy, it is highly nonconvex and must be dealt with with caution. A detection algorithm is proposed that capitalizes on compressed sensing results and on the generalized distributive law (message passing on factor graphs).

https://ieeexplore.ieee.org/document/8683233

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