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- W2912471387 abstract "This work provides a complete framework, including device, architecture, and algorithm, for implementing bio-inspired supervised spiking neural networks (SNNs) on hardware. An analog synapse with atypical dual bipolar resistive-switching (D-BRS) modes demonstrates interchangeable Hebbian spiking-timing-dependent plasticity (STDP) and anti-Hebbian STDP, and it is capable of implementing supervised ReSuMe SNNs in crossbar arrays. By using an “exchange” update scheme, accurate supervised learning (~96% for MNIST) is achieved in a compact network." @default.
- W2912471387 created "2019-02-21" @default.
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- W2912471387 date "2018-12-01" @default.
- W2912471387 modified "2023-09-30" @default.
- W2912471387 title "Interchangeable Hebbian and Anti-Hebbian STDP Applied to Supervised Learning in Spiking Neural Network" @default.
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- W2912471387 doi "https://doi.org/10.1109/iedm.2018.8614648" @default.
- W2912471387 hasPublicationYear "2018" @default.
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