Title:
Implementation of the locally competitive algorithm on a field programmable analog array
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 | |
relation.isAdvisorOfPublication | da2ccc86-1c57-49e7-b766-ceb2f9a4eac5 | |
relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
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