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dc.contributor.advisorHasler, Jennifer
dc.contributor.authorShah, Sahil Sandeep
dc.date.accessioned2018-05-31T18:16:12Z
dc.date.available2018-05-31T18:16:12Z
dc.date.created2018-05
dc.date.issued2018-04-10
dc.date.submittedMay 2018
dc.identifier.urihttp://hdl.handle.net/1853/59918
dc.description.abstractThis work investigates low-power mixed-signal computation techniques for real-time applications. The need for real-time processing, with rise of wearable devices, creates a strong drive for researching and developing methods and system architectures which reduces the power consumption. By performing the computation locally near the sensor node one can increase the energy efficiency of such devices by reducing the need for communication to the cloud. Analog computation has shown promising results in this space by significantly reducing power consumption by processing signals in analog without having to convert them into the digital domain. Further, by adding programmability and configurability to analog, the effects of process, voltage, and temperature variations could be reduced significantly.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectLow-power computation
dc.subjectFPAA
dc.subjectWearable devices
dc.titleLow-power computation using FPAA for wearable devices
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentElectrical and Computer Engineering
thesis.degree.levelDoctoral
dc.contributor.committeeMemberInan, Omer
dc.contributor.committeeMemberSarioglu, Fatih
dc.contributor.committeeMemberKhan, Asif I.
dc.contributor.committeeMemberMinch, Bradley
dc.date.updated2018-05-31T18:16:12Z


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