Journal
FRONTIERS IN NANOTECHNOLOGY
Volume 3, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fnano.2021.675792
Keywords
atomic switch networks; memristive; neuromorphic; reservoir computing; in-materio
Funding
- World Premier International Center for Materials Nanoarchitectonics (MANA) at the National Institute for Materials Science (Tsukuba, Japan)
- National Science Foundation Graduate Research Fellowship
- Semiconductor Research Corp. [2015,209,024]
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The study utilized Atomic Switch Networks consisting of silver iodide (AgI) junctions as a neuromorphic substrate for physical Reservoir Computing, achieving high accuracy in classifying spoken digit audio data, thereby expanding the viable memristive materials for functional nanowire networks.
Atomic Switch Networks comprising silver iodide (AgI) junctions, a material previously unexplored as functional memristive elements within highly interconnected nanowire networks, were employed as a neuromorphic substrate for physical Reservoir Computing This new class of ASN-based devices has been physically characterized and utilized to classify spoken digit audio data, demonstrating the utility of substrate-based device architectures where intrinsic material properties can be exploited to perform computation in-materio. This work demonstrates high accuracy in the classification of temporally analyzed Free-Spoken Digit Data These results expand upon the class of viable memristive materials available for the production of functional nanowire networks and bolster the utility of ASN-based devices as unique hardware platforms for neuromorphic computing applications involving memory, adaptation and learning.
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