Please use this identifier to cite or link to this item: http://drsr.daiict.ac.in//handle/123456789/399
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dc.contributor.advisorZaveri, Mazad S
dc.contributor.authorAmbasana, Nikita B.
dc.date.accessioned2017-06-10T14:39:57Z
dc.date.available2017-06-10T14:39:57Z
dc.date.issued2012
dc.identifier.citationAmbasana, Nikita B. (2012). FPGA implementation of environment/noise classification using neural networks. Dhirubhai Ambani Institute of Information and Communication Technology, ix, 42 p. (Acc.No: T00362)
dc.identifier.urihttp://drsr.daiict.ac.in/handle/123456789/399
dc.description.abstractThe purpose of this thesis is to give an insight into the implementation of a system of neural networks, for the tasks of Noise/Environment Modeling, Feature Extraction and Classification of Noise/Environment, on a Field Programmable Gate Array (FPGA). A methodology for creating baseline architecture for a new system of neural networks has been followed, to give worst case estimates. After necessary analysis an estimate of hardware utilization, within a specific FPGA (XC3S250E Spartan 3E Device) and the Time for Computation, for each of the machines used, is given. It also summarizes the Performance-Price Ratio in terms of Time of Computation and Hardware for Logic simplementation, for different degrees of parallelism in the system.
dc.publisherDhirubhai Ambani Institute of Information and Communication Technology
dc.subjectFPGA
dc.subjectField Programmable Gate Array
dc.subjectNeural networks
dc.classification.ddc006.32 AMB
dc.titleFPGA implementation of environment/noise classification using neural networks
dc.typeDissertation
dc.degreeM. Tech
dc.student.id201011031
dc.accession.numberT00362
Appears in Collections:M Tech Dissertations

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