Implementation of the locally competitive algorithm on a field programmable analog array

dc.contributor.advisor Hasler, Jennifer
dc.contributor.author Balavoine, Aurèle en_US
dc.contributor.committeeMember Anderson, David
dc.contributor.committeeMember Rozell, Christopher
dc.contributor.department Electrical and Computer Engineering en_US
dc.date.accessioned 2011-03-04T21:01:43Z
dc.date.available 2011-03-04T21:01:43Z
dc.date.issued 2009-11-17 en_US
dc.description.abstract Sparse approximation is an important class of optimization problem in signal and image processing applications. This thesis presents an analog solution to this problem, based on the Locally Competitive Algorithm (LCA). A Hopfield-Network-like analog system, operating on sub-threshold currents is proposed as a solution. The results of the circuit components' implementation on the RASP2.8a chip, a Field Programmable Analog Array, are presented. en_US
dc.description.degree M.S. en_US
dc.identifier.uri http://hdl.handle.net/1853/37255
dc.publisher Georgia Institute of Technology en_US
dc.subject FPAA en_US
dc.subject Sparse approximation en_US
dc.subject LCA en_US
dc.subject Non-linear optimization en_US
dc.subject Hopfield neural networks en_US
dc.subject.lcsh Signal processing
dc.subject.lcsh Neural networks (Computer science)
dc.title Implementation of the locally competitive algorithm on a field programmable analog array en_US
dc.type Text
dc.type.genre Thesis
dspace.entity.type Publication
local.contributor.advisor Hasler, Jennifer
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
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