The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
TiO x-Based RRAM Synapse With 64-Levels of Conductance and Symmetric Conductance Change by Adopting a Hybrid Pulse Scheme for Neuromorphic Computing
Abstract
We propose TiOx-based resistive switching device for neuromorphic synapse applications. This device is capable of 64-levels conductance states because of their optimized interface between the metal electrode and the TiOx film. To compensate the change in switching power with increasing pulse number, we propose the use of fixed voltage and current pulses in potentiation and depression conditions, respectively. By adopting a hybrid pulse scheme, the symmetry of conductance change under both potentiation and depression conditions is shown to be significantly improved. Both the improved conductance levels and the symmetry of conductance change are directly related with enhanced pattern recognition accuracy, which is confirmed by a neural network simulation.
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Burr, G. W., Shelby, R. M., Sidler, S., di Nolfo, C., Jang, J., Boybat, I., Shenoy, R. S., Narayanan, P., Virwani, K., Giacometti, E. U., et al. (2015) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2015.2439635 · Cited by 936
Self-citationA single-transistor silicon synapse
Diorio, C., Hasler, P., Minch, A., & Mead, C. A. (1996) · IEEE Transactions on Electron Devices · doi:10.1109/16.543035 · Cited by 360 · cited 1×
“various electronic synaptic devices have been proposed, such as single transistors [3], phase change memory [1], ferroelectric random access memory [4], and resistive random access memory (RRAM) [5]–[7].”
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Cited by
Analogue signal and image processing with large memristor crossbars
Li, C., Hu, M., Li, Y., Jiang, H., Ge, N., Montgomery, E., Zhang, J., Song, W., Dávila, N., Graves, C. E., et al. (2017) · Nature Electronics · doi:10.1038/s41928-017-0002-z · Cited by 1,292
Fully memristive neural networks for pattern classification with unsupervised learning
Wang, Z., Joshi, S., Savel’ev, S., Song, W., Midya, R., Li, Y., Rao, M., Yan, P., Asapu, S., Zhuo, Y., et al. (2018) · Nature Electronics · doi:10.1038/s41928-018-0023-2 · Cited by 1,106
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
Reliability of analog resistive switching memory for neuromorphic computing
Zhao, M., Gao, B., Tang, J., Qian, H., & Wu, H. (2020) · Applied Physics Reviews · doi:10.1063/1.5124915 · Cited by 349
Memory materials and devices: From concept to application
Zhang, Z., Wang, Z., Shi, T., Bi, C., Rao, F., Cai, Y., Liu, Q., Wu, H., & Zhou, P. (2020) · InfoMat · doi:10.1002/inf2.12077 · Cited by 258
Metadata
- Authors
- Park, J., Kwak, M., Moon, K., Woo, J., Lee, D., & Hwang, H.
- Venue
- IEEE Electron Device Letters
- Published
- 2016-12
- Volume
- 37
- Issue
- 12
- Pages
- 1559-1562
- ISSN
- 0741-3106 (ISSN-L)
- 1558-0563
- OpenAlex
- W2543328879
- Cited by
- 225
- References
- 2
- FWCI
- 8.99
- Type
- journal article
- Language
- en
- Open access
- closed
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- Park, J., Kwak, M., Moon, K., Woo, J., Lee, D., & Hwang, H. (2016). TiO x-Based RRAM Synapse With 64-Levels of Conductance and Symmetric Conductance Change by Adopting a Hybrid Pulse Scheme for Neuromorphic Computing. IEEE Electron Device Letters. https://doi.org/10.1109/led.2016.2622716
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