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MS Final Exam – Shashini De Silva

Coupled Compressive Sensing : Sequential Reinforcement Approach

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

Major Advisor: Jinsub Kim
Committee: Eduardo Cotilla-Sanchez
Committee: Raviv Raich
Committee: Xiaoli Fern
GCR: Len Coop

Wednesday, November 14 at 2:00pm to 4:00pm

Kelley Engineering Center, 1007
110 SW Park Terrace, Corvallis, OR 97331

Event Type

Lecture or Presentation

Event Topic

Research

Organization
College of Engineering, Electrical Engineering and Computer Science
Contact Name

Calvin Hughes

Contact Email

Calvin.Hughes@oregonstate.edu

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