Data di Pubblicazione:
2019
Abstract:
Optical neuromorphic computing processes information at the speed of light, but requires a careful design and fabrication of the deep layers, which strongly hampers the development of large-scale photonic learning machines [1,2]. New paradigms, as reservoir computing [3], suggest that brain-inspired complex systems such as disordered and biological materials may realize artificial neural networks with thousands of computational nodes trained only at the input and at the readout.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Biological materials; Neural networks
Elenco autori:
Marcucci, Giulia; Pierangeli, Davide; Conti, Claudio
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