The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability
Open accessAbstract
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.
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Cites
Mastering the game of Go with deep neural networks and tree search
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Self-citationNanoscale Memristor Device as Synapse in Neuromorphic Systems
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“…operations, including long-term potentiation/depression (LTP/LTD), short-term potentiation/depression, a spike-timing-dependent plasticity (STDP) learning rule, paired-pulse facilitation (PPF), and low-power consumption, have been extensively simulated or emulated in a single device 10 – 21 .”
BackgroundA million spiking-neuron integrated circuit with a scalable communication network and interface
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Self-citationMemristive switching mechanism for metal/oxide/metal nanodevices
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“…alteration of the bulk insulator ’ s resistivity due to the migration of ions or to a trapping-releasing process of carriers 37, 38 , the modi fi cation of the metal/insulator interface ’ s resistivity 39 , and the formation of localized metal-atom chains bridging the electrode materials 26, 40 .”
BackgroundSelf-citationMemristors with diffusive dynamics as synaptic emulators for neuromorphic computing
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Self-citation‘Memristive’ switches enable ‘stateful’ logic operations via material implication
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Short-term plasticity and long-term potentiation mimicked in single inorganic synapses
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Cited by
A comprehensive review on emerging artificial neuromorphic devices
Zhu, J., Zhang, T., Yang, Y., & Huang, R. (2020) · Applied Physics Reviews · doi:10.1063/1.5118217 · Cited by 758
Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics
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Neuro-inspired electronic skin for robots
Liu, F., Deswal, S., Christou, A., Sandamirskaya, Y., Kaboli, M., & Dahiya, R. (2022) · Science Robotics · doi:10.1126/scirobotics.abl7344 · Cited by 300
Metadata
- Authors
- Wu, C., Kim, T. W., Choi, H. Y., Strukov, D. B., & Yang, J. J.
- Venue
- Nature Communications
- Published
- 2017-09-29
- Volume
- 8
- Issue
- 1
- Pages
- 752-752
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2760117628
- Cited by
- 320
- References
- 43
- FWCI
- 13.43
- Type
- journal article
- Language
- en
- Open access
- gold
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