2022
DOI: 10.1002/aisy.202100236
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Emerging Optical In‐Memory Computing Sensor Synapses Based on Low‐Dimensional Nanomaterials for Neuromorphic Networks

Abstract: Emerging optical synapses with in‐memory computing sensor (IMCS) performance are considered to be one of the most effective candidates to circumvent the bottleneck of the current Von Neumann structure while developing neuromorphic systems with higher effectiveness and lower energy consumption. Biomimetic properties of optical IMCS synapses in function and form indicate the higher requirements for utilized functional materials, such as stronger optical sensitivity and lower energy dissipation. Because of proper… Show more

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Cited by 22 publications
(8 citation statements)
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“…The multistate switching behavior is uniform and reproducible for 50 cycles, as demonstrated in Figure b. Such behavior suggests that our hybrid memristor devices have promising potential as candidates of artificial synapses for neuromorphic computing and multilevel data storage applications. Such CC level-dependent control has been widely demonstrated in resistive switching memories and can be ascribed by the formation of filaments with different dimensions across the device. , Although similar multistate switching behavior was previously observed in our crossbar GeSbTe-based memory devices, the ON/OFF resistance ratio was smaller (by about 1 order of magnitude), and the CC was needed for both the SET and RESET processes to protect the devices. ,, …”
Section: Resultssupporting
confidence: 73%
“…The multistate switching behavior is uniform and reproducible for 50 cycles, as demonstrated in Figure b. Such behavior suggests that our hybrid memristor devices have promising potential as candidates of artificial synapses for neuromorphic computing and multilevel data storage applications. Such CC level-dependent control has been widely demonstrated in resistive switching memories and can be ascribed by the formation of filaments with different dimensions across the device. , Although similar multistate switching behavior was previously observed in our crossbar GeSbTe-based memory devices, the ON/OFF resistance ratio was smaller (by about 1 order of magnitude), and the CC was needed for both the SET and RESET processes to protect the devices. ,, …”
Section: Resultssupporting
confidence: 73%
“…The recognition accuracy exhibits enough fault-tolerance capability to apply to an artificial neural network for the visual system. 12…”
Section: Resultsmentioning
confidence: 99%
“…Different types of LTP behaviors, such as spike timing-dependent plasticity (STDP) (Fig. 5e), spike ratedependent plasticity (SRDP), and spike number-dependent plasticity (SNDP), 145,146 have been reported in artificial synaptic devices.…”
Section: Biological System and Its Emulation Propertiesmentioning
confidence: 99%