Accelerating Gauss-Newton filters on FPGA's

 

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dc.contributor.advisor Inggs, Michael en_ZA
dc.contributor.author Da Conceicao, Jean-Paul Costa en_ZA
dc.date.accessioned 2014-12-28T14:40:54Z
dc.date.available 2014-12-28T14:40:54Z
dc.date.issued 2010 en_ZA
dc.identifier.citation Da Conceicao, J. 2010. Accelerating Gauss-Newton filters on FPGA's. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/10329
dc.description Includes bibliographical references (leaves 123-128). en_ZA
dc.description.abstract Radar tracking filters are generally computationally expensive, involving the manipulation of large matrices and deeply nested loops. In addition, they must generally work in real-time to be of any use. The now-common Kalman Filter was developed in the 1960's specifically for the purposes of lowering its computational burden, so that it could be implemented using the limited computational resources of the time. However, with the exponential increases in computing power since then, it is now possible to reconsider more heavy-weight, robust algorithms such as the original nonrecursive Gauss-Newton filter on which the Kalman filter is based. This dissertation investigates the acceleration of such a filter using FPGA technology, making use of custom, reduced-precision number formats. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Electrical Engineering en_ZA
dc.title Accelerating Gauss-Newton filters on FPGA's en_ZA
dc.type Thesis / Dissertation en_ZA
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Engineering & the Built Environment en_ZA
dc.publisher.department Department of Electrical Engineering en_ZA
dc.type.qualificationlevel Masters en_ZA
dc.type.qualificationname MSc en_ZA
uct.type.filetype Text
uct.type.filetype Image


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