Paper Info
Title
Memristor-based synapse design and a case study in reconfigurable systems
Abstract
Scientists have dreamed of an information system with cognitive human-like skills for years. However, constrained by the device characteristics and rapidly increasing design complexity under the traditional processing technology, little progress has been made in hardware implementation. The recently popularized memristor offers a potential breakthrough for neuromorphic computing because of its unique properties including nonvolatily, extremely high fabrication density, and sensitivity to historic voltage/current behavior. In this work, we first investigate the memristor-based synapse design and the corresponding training scheme. Then, a case study of an 8-bit arithmetic logic unit (ALU) design is used to demonstrate the hardware implementation of reconfigurable system built based on memristor synapses.
Year
DOI
Venue
2013
10.1109/IJCNN.2013.6706776
IJCNN
Keywords
Field
DocType
logic circuits,neuromorphic computing,arithmetic logic unit (alu),information system,synapse network,hardware implementation,cognitive human-like skills,design complexity,fabrication density,digital arithmetic,computational complexity,memristor-based synapse design,8-bit arithmetic logic unit design,logic design,alu,reconfigurable system,memristors,memristor,reconfigurable systems,historic voltage-current behavior
Logic synthesis,Information system,Logic gate,Computer science,Arithmetic logic unit,Neuromorphic engineering,Theoretical computer science,Artificial intelligence,Memistor,Computer architecture,Memristor,Machine learning,Computational complexity theory
Conference
ISSN
ISBN
Citations 
2161-4393
978-1-4673-6128-6
0
PageRank 
References 
Authors
0.34
8
5
Name
Order
Citations
PageRank
Feng Ji100.34
Hai Li22435208.37
Bryant T. Wysocki3656.76
Clare Thiem4102.06
Nathan R. McDonald5877.03