An Analytical Comparison of Locally-Connected Reconfigurable Neural Network Architectures Using a C. elegans Locomotive Model

An Analytical Comparison of Locally-Connected Reconfigurable Neural Network Architectures Using a C. elegans Locomotive Model

The scale of modern neural networks is growing rapidly, with direct hardware implementations providing significant speed and energy improvements over their software counterparts. However, these hardware implementations frequently assume global connectivity between neurons and thus suffer from commun...

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Bibliographic Details
Main Authors: Jonathan Graham-Harper-Cater, Benjamin Metcalfe, Peter Wilson
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Computers
Subjects:
reconfigurable
architecture
neural-network
neuromorphic
FPGA
C. elegans
Online Access:http://www.mdpi.com/2073-431X/7/3/43

Internet

http://www.mdpi.com/2073-431X/7/3/43

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