期刊
NATURE COMMUNICATIONS
卷 9, 期 -, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/s41467-018-05517-6
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资金
- European Research Council [321160]
- Science Foundation Ireland (SFI) AMBER Centre [SFI/12/RC/2278]
- SFI ivP Grant [12/IA/1482]
- European Research Council (ERC) [321160] Funding Source: European Research Council (ERC)
Nanowire networks are promising memristive architectures for neuromorphic applications due to their connectivity and neurosynaptic-like behaviours. Here, we demonstrate a selfsimilar scaling of the conductance of networks and the junctions that comprise them. We show this behavior is an emergent property of any junction-dominated network. A particular class of junctions naturally leads to the emergence of conductance plateaus and a winner-takes-all conducting path that spans the entire network, and which we show corresponds to the lowest-energy connectivity path. The memory stored in the conductance state is distributed across the network but encoded in specific connectivity pathways, similar to that found in biological systems. These results are expected to have important implications for development of neuromorphic devices based on reservoir computing.
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