Article ; Online: Physical reservoirs based on MoS
Nanoscale horizons
2024 Volume 9, Issue 5, Page(s) 752–763
Abstract: Reservoir computing (RC), a variant of recurrent neural networks (RNNs), is well-known for its reduced energy consumption through exclusive focus on training the output weight and its superior performance in handling spatiotemporal information. ... ...
Abstract | Reservoir computing (RC), a variant of recurrent neural networks (RNNs), is well-known for its reduced energy consumption through exclusive focus on training the output weight and its superior performance in handling spatiotemporal information. Implementing these networks in hardware requires devices with superior fading memory behavior. Unlike filament-based two-terminal devices, those relying on ferroelectric switching demonstrate improved voltage reliability, while three-terminal transistors provide additional active control. HfO |
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Language | English |
Publishing date | 2024-04-29 |
Publishing country | England |
Document type | Journal Article |
ISSN | 2055-6764 |
ISSN (online) | 2055-6764 |
DOI | 10.1039/d3nh00524k |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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