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Title: Sound Sensing System Using Machine Learning Accelerator
Authors: Ashraf, Ammad
Advisors: Verma, Naveen
Department: Electrical Engineering
Class Year: 2017
Abstract: Machine learning allows for us to interact with data in a meaningful way on a very large scale. A the amount data available to us grows, so does the potential of machine learning. However, there is a drawback in that the computations needed to draw conclusions from this data can be extremely expensive. This paper explores a potential use of a machine learning accelerator that allows us to do these computations in a more efficient manner.
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Electrical Engineering, 1932-2020

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