| Literature DB >> 31341103 |
Sridhar Chandrasekaran1, Firman Mangasa Simanjuntak, R Saminathan, Debashis Panda, Tseung-Yuen Tseng.
Abstract
Artificial synapse having good linearity is crucial to achieve an efficient learning process in neuromorphic computing. It is found that the synaptic linearity can be enhanced by engineering the doping region across the switching layer. The nonlinearity of potentiation and depression of the pure device is 36% and 91%, respectively; meanwhile, the nonlinearity after doping can be suppressed to be 22% (potentiation) and 60% (depression). Henceforth, the learning accuracy of the doped device is 91% with only 13 iterations; meanwhile, the pure device is 78%. A detailed conduction mechanism to understand this phenomenon is proposed.Entities:
Year: 2019 PMID: 31341103 DOI: 10.1088/1361-6528/ab3480
Source DB: PubMed Journal: Nanotechnology ISSN: 0957-4484 Impact factor: 3.874