PORTO @ Archivio Istituzionale della Ricerca

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Neuromorphic computing aims at the realization of intelligent systems able to process information similarly to our brain. Brain-inspired computing paradigms have been implemented in crossbar arrays of memristive devices; however, this approach does not emulate the topology and the emergent behaviour of biological neuronal circuits, where the principle of self-organization regulates both structure and function. Here, we report on in materia reservoir computing in a fully memristive architecture based on self-organized nanowire networks. Thanks to the functional synaptic connectivity with nonlinear dynamics and fading memory properties, the designless nanowire complex network acts as a network-wide physical reservoir able to map spatio-temporal inputs into a feature space that can be analysed by a memristive resistive switching memory read-out layer. Computing capabilities, including recognition of spatio-temporal patterns and time-series prediction, show that the emergent memristive behaviour of nanowire networks allows in materia implementation of brain-inspired computing paradigms characterized by a reduced training cost.

In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks / Milano, G.; Pedretti, G.; Montano, K.; Ricci, S.; Hashemkhani, S.; Boarino, L.; Ielmini, D.; Ricciardi, C.. - In: NATURE MATERIALS. - ISSN 1476-1122. - ELETTRONICO. - 21:(2022), pp. 195-202. [10.1038/s41563-021-01099-9]

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