Emerging Memristive Artificial Synapses and Neurons for Energy-Efficient Neuromorphic Computing.
Sign Up to like & getrecommendations! Published in 2020 at "Advanced materials"
DOI: 10.1002/adma.202004659
Abstract: Memristors have recently attracted significant interest due to their applicability as promising building blocks of neuromorphic computing and electronic systems. The dynamic reconfiguration of memristors, which is based on the history of applied electrical stimuli,… read more here.
Keywords: energy efficient; artificial synapses; efficient neuromorphic; synapses neurons ... See more keywords
Heterosynaptic MoS2 Memtransistors Emulating Biological Neuromodulation for Energy-Efficient Neuromorphic Electronics.
Sign Up to like & getrecommendations! Published in 2023 at "Advanced materials"
DOI: 10.1002/adma.202211525
Abstract: Heterosynaptic neuromodulation is a key enabler for energy-efficient and high-level biological neural processing. However, such manifold synaptic modulation cannot be emulated using conventional memristors and synaptic transistors. Thus, herein, we report a three-terminal heterosynaptic memtransistor… read more here.
Keywords: energy; biological neuromodulation; efficient neuromorphic; neuromorphic electronics ... See more keywords
Floating-Gate Synaptic Transistors for Energy-Efficient Neuromorphic Computing.
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DOI: 10.1002/adma.202515605
Abstract: By integrating nonvolatile memory and processing, floating-gate synaptic transistors (FGSTs) have emerged as a pivotal platform for energy-efficient neuromorphic computing, overcoming limitations inherent in conventional Von Neumann architectures. These devices utilize a unique floating-gate layer… read more here.
Keywords: efficient neuromorphic; energy; energy efficient; synaptic transistors ... See more keywords
The coexistence of threshold and memory switching characteristics of ALD HfO2 memristor synaptic arrays for energy-efficient neuromorphic computing.
Sign Up to like & getrecommendations! Published in 2020 at "Nanoscale"
DOI: 10.1039/d0nr02335c
Abstract: The development of bioinspired electronic devices that can mimic the biological synapses is an essential step towards the development of efficient neuromorphic systems to simulate the functions of the human brain. Among various materials that… read more here.
Keywords: synaptic arrays; memory switching; memristor synaptic; coexistence threshold ... See more keywords
Efficient Neuromorphic Hardware Through Spiking Temporal Online Local Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Very Large Scale Integration (VLSI) Systems"
DOI: 10.1109/tvlsi.2022.3208191
Abstract: Local learning schemes have shown promising performance in spiking neural networks (SNNs) training and are considered a step toward more biologically plausible learning. Despite many efforts to design high-performance neuromorphic systems, a fast and efficient… read more here.
Keywords: neuromorphic hardware; hardware; training; local learning ... See more keywords