A system design approach to neuromorphic classifiers

Author(s)
Ramakrishnan, Shubha
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Abstract
This work considers alternative strategies to mainstream digital approaches to signal processing - namely analog and neuromorphic solutions, for increased computing efficiency. In the context of a speech recognizer application, we use low-power analog approaches for the signal conditioning and basic auditory feature extraction, while using a neuromorphic IC for building a dendritic classifier that can be used as a low-power word spotter. In doing so, this work also aspires to posit the significance of dendrites in neural computation.
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Date
2013-01-09
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Text
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Dissertation
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