Coupled Compressive Sensing : Sequential Reinforcement Approach

Graduate Thesis Or Dissertation

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Citeable URL: https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/12579z442

Descriptions

Attribute Name	Values
Creator	De Silva, Shashini A.
Abstract	We consider multiple Compressive Sensing (CS) problems wherein the supports of signal vectors of CS problems are restricted to satisfy a collection of joint logical constraints, which we refer to as coupling constraints. We consider a case where the coupling constraints are encoded in a graph and present a sequential reinforcement approach to solve the multiple CS problems efficiently. In the sequential reinforcement approach, we iteratively select and solve one CS problem that we can solve with the highest confidence level and use the recovered signal supports to reinforce the correct support recovery of remaining CS problems. The efficacy of the proposed approach is validated using the experiments with a synthetic problem and power network topology identification of IEEE 14 bus network.
License	All rights reserved
Resource Type	Masters Thesis
Date Issued	2018-11-14
Degree Level	Master's
Degree Name	Master of Science (M.S.)
Degree Field	Electrical and Computer Engineering
Degree Grantor	Oregon State University
Commencement Year	2019
Advisor	Kim, Jinsub
Committee Member	Raich, Raviv Fern, Xiaoli Cotilla-Sanchez, Eduardo
Academic Affiliation	Electrical Engineering and Computer Science
Rights Statement	In Copyright
Publisher	Oregon State University
Peer Reviewed	No
Language	English [eng]
Embargo date range	2019-01-09 to 2021-02-10

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