Avalanches and edge-of-chaos learning in neuromorphic nanowire networks.

ABSTRACT: The brain's efficient information processing is enabled by the interplay between its neuro-synaptic elements and complex network structure. This work reports on the neuromorphic dynamics of nanowire networks (NWNs), a unique brain-inspired system with synapse-like memristive junctions embedded within a recurrent neural network-like structure. Simulation and experiment elucidate how collective memristive switching gives rise to long-range transport pathways, drastically altering the network's global state via a discontinuous phase transition. The spatio-temporal properties of switching dynamics are found to be consistent with avalanches displaying power-law size and life-time distributions, with exponents obeying the crackling noise relationship, thus satisfying criteria for criticality, as

SUBMITTER: Hochstetter J 

PROVIDER: S-EPMC8242064 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature