2024
DOI: 10.1073/pnas.2318362121
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Neuromorphic one-shot learning utilizing a phase-transition material

Alessandro R. Galloni,
Yifan Yuan,
Minning Zhu
et al.

Abstract: Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by thresh… Show more

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Cited by 4 publications
(1 citation statement)
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“…The origin of the thermal phase transition is debated in the literature between Peierls vs Mott mechanisms concerning the role of lattice versus electron density . The volatile resistive switching due to the MIT in pristine VO 2 films can be exploited to emulate rich neuronal dynamics, including spike-timing dependent plasticity (STDP) and behavioral time scale synaptic plasticity (BTSP). , …”
Section: Proton-conducting Neuromorphic Devicesmentioning
confidence: 99%
“…The origin of the thermal phase transition is debated in the literature between Peierls vs Mott mechanisms concerning the role of lattice versus electron density . The volatile resistive switching due to the MIT in pristine VO 2 films can be exploited to emulate rich neuronal dynamics, including spike-timing dependent plasticity (STDP) and behavioral time scale synaptic plasticity (BTSP). , …”
Section: Proton-conducting Neuromorphic Devicesmentioning
confidence: 99%