@inproceedings{488583c504914363ac75af9476a8ad30,
title = "Basis pursuit in sensor networks",
abstract = "Basis Pursuit (BP) finds a minimum ℓ1-norm vector z that satisfies the underdetermined linear system Mz = b, where the matrix M and vector b are given. Lately, BP has attracted attention because of its application in compressed sensing, where it is used to reconstruct signals by finding the sparsest solutions of linear systems. In this paper, we propose a distributed algorithm to solve BP. This means no central node is used for the processing and no node has access to all the data: the rows of M and the vector b are distributed over a set of interconnected compute nodes. A typical scenario is a sensor network. The novelty of our method is in using an optimal first-order method to solve an augmented Lagrangian-based reformulation of BP. We implemented our algorithm in a computer cluster, and show that it can solve problems that are too large to be stored in and processed by a single node.",
keywords = "basis pursuit, compressed sensing, Convex optimization, distributed algorithm, sensor network",
author = "Mota, {Jo{\~a}o F. C.} and Xavier, {Jo{\~a}o M. F.} and Aguiar, {Pedro M. Q.} and Markus P{\"u}schel",
year = "2011",
month = jul,
day = "12",
doi = "10.1109/ICASSP.2011.5946267",
language = "English",
isbn = "9781457705380",
series = "IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
publisher = "IEEE",
pages = "2916--2919",
booktitle = "2011 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)",
address = "United States",
note = "36th IEEE International Conference on Acoustics, Speech, and Signal Processing 2011, ICASSP 2011 ; Conference date: 22-05-2011 Through 27-05-2011",
}