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Massachusetts Institute of Technology

Sparse recovery and Fourier sampling

Abstract

dc:description.abstract

In the last decade a broad literature has arisen studying sparse recovery, the estimation of sparse vectors from low dimensional linear projections. Sparse recovery has a wide variety of applications such as streaming algorithms, image acquisition, and disease testing. A particularly important subclass of sparse recovery is the sparse Fourier transform, which considers the computation of a discrete Fourier transform when the output is sparse. Applications of the sparse Fourier transform include medical imaging, spectrum sensing, and purely computation tasks involving convolution. This thesis describes a coherent set of techniques that achieve optimal or near-optimal upper and lower bounds for a variety of sparse recovery problems. We give the following state-of-the-art algorithms for recovery of an approximately k-sparse vector in n dimensions: -- Two sparse Fourier transform algorithms, respectively taking ... time and ... samples. The latter is within log e log n of the optimal sample complexity when ... -- An algorithm for adaptive sparse recovery using ... measurements, showing that adaptivity can give substantial improvements when k is small. -- An algorithm for C-approximate sparse recovery with ... measurements, which matches our lower bound up to the log* k factor and gives the first improvement for ... In the second part of this thesis, we give lower bounds for the above problems and more.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Price, Eric C
Advisor dc:contributor.advisor
  • Piotr Indyk.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/85458
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/85458

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Price, Eric C. Sparse recovery and Fourier sampling. Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85458