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Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability

Title
Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability
Author
김태환
Keywords
ORGANIC NONVOLATILE MEMORY; DEVICE
Issue Date
2017-09
Publisher
NATURE PUBLISHING GROUP
Citation
NATURE COMMUNICATIONS, v. 8, Article no. 752
Abstract
If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures impedes the achievement of three-dimensional interconnectivity, high-device density, or flexibility. Here we report flexible three-dimensional artificial chemical synapse networks, in which two-terminal memristive devices, namely, electronic synapses (e-synapses), are connected by vertically stacking crossbar electrodes. The e-synapses resemble the key features of biological synapses: unilateral connection, long-term potentiation/depression, a spike-timing-dependent plasticity learning rule, paired-pulse facilitation, and ultralow-power consumption. The three-dimensional artificial synapse networks enable a direct emulation of correlated learning and trainable memory capability with strong tolerances to input faults and variations, which shows the feasibility of using them in futuristic electronic devices and can provide a physical platform for the realization of smart memories and machine learning and for operation of the complex algorithms involving hierarchical neural networks.
URI
https://www.nature.com/articles/s41467-017-00803-1https://repository.hanyang.ac.kr/handle/20.500.11754/115441
ISSN
2041-1723
DOI
10.1038/s41467-017-00803-1
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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