The DOI matches its Crossref record; 215 of the 215 references it cites were found in a registry or an index.
Brain-inspired computing with memristors: Challenges in devices, circuits, and systems
Abstract
This article provides a review of current development and challenges in brain-inspired computing with memristors. We review the mechanisms of various memristive devices that can mimic synaptic and neuronal functionalities and survey the progress of memristive spiking and artificial neural networks. Different architectures are compared, including spiking neural networks, fully connected artificial neural networks, convolutional neural networks, and Hopfield recurrent neural networks. Challenges and strategies for nanoelectronic brain-inspired computing systems, including device variations, training, and testing algorithms, are also discussed.
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Cites
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A million spiking-neuron integrated circuit with a scalable communication network and interface
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Cited by
2D Material Based Synaptic Devices for Neuromorphic Computing
Cao, G., Meng, P., Chen, J., Liu, H., Bian, R., Zhu, C., Liu, F., & Liu, Z. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202005443 · Cited by 382
Hardware Implementation of Neuromorphic Computing Using Large‐Scale Memristor Crossbar Arrays
Li, Y., & Ang, K.-W. (2021) · Advanced Intelligent Systems · doi:10.1002/aisy.202000137 · Cited by 220
Nanostructured perovskites for nonvolatile memory devices
Liu, Q., Gao, S., Xu, L., Yue, W., Zhang, C., Kan, H., Li, Y., & Shen, G. (2022) · Chemical Society Reviews · doi:10.1039/d1cs00886b · Cited by 163
Metadata
- Authors
- Zhang, Y., Wang, Z., Zhu, J., Yang, Y., Rao, M., Song, W., Zhuo, Y., Zhang, X., Cui, M., Shen, L., Huang, R., & Joshua Yang, J.
- Venue
- Applied Physics Reviews
- Publisher
- AIP Publishing
- Published
- 2020-01-16
- Volume
- 7
- Issue
- 1
- ISSN
- 1931-9401 (ISSN-L)
- OpenAlex
- W2999474720
- Cited by
- 384
- References
- 215
- FWCI
- 19.07
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, Y., Wang, Z., Zhu, J., Yang, Y., Rao, M., Song, W., Zhuo, Y., Zhang, X., Cui, M., Shen, L., Huang, R., & Joshua Yang, J. (2020). Brain-inspired computing with memristors: Challenges in devices, circuits, and systems. Applied Physics Reviews. https://doi.org/10.1063/1.5124027
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
