A comprehensive review on emerging artificial neuromorphic devices
The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …
efficiency and ultralow power consumption. In the past few decades, neuromorphic …
Bridging biological and artificial neural networks with emerging neuromorphic devices: fundamentals, progress, and challenges
As the research on artificial intelligence booms, there is broad interest in brain‐inspired
computing using novel neuromorphic devices. The potential of various emerging materials …
computing using novel neuromorphic devices. The potential of various emerging materials …
Neuromemristive circuits for edge computing: A review
O Krestinskaya, AP James… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …
network of sensors connected to Internet pose challenges for power management …
Ferroelectric tunneling junctions based on aluminum oxide/zirconium-doped hafnium oxide for neuromorphic computing
Ferroelectric tunneling junctions (FTJs) with tunable tunneling electroresistance (TER) are
promising for many emerging applications, including non-volatile memories and …
promising for many emerging applications, including non-volatile memories and …
[HTML][HTML] Pathways to efficient neuromorphic computing with non-volatile memory technologies
Historically, memory technologies have been evaluated based on their storage density, cost,
and latencies. Beyond these metrics, the need to enable smarter and intelligent computing …
and latencies. Beyond these metrics, the need to enable smarter and intelligent computing …
3D trigonal FAPbI3‐based multilevel resistive switching nonvolatile memory for artificial neural synapse
L Tao, B Jiang, S Ma, Y Zhang, Y Huang, Y Pan… - …, 2024 - Wiley Online Library
Hybrid perovskites have attracted enormous attention in the next generation resistive
switching (RS) memristor for the artificial synapses, owing to their ambipolar charge …
switching (RS) memristor for the artificial synapses, owing to their ambipolar charge …
Analog‐type resistive switching devices for neuromorphic computing
Brain‐inspired neuromorphic computing has attracted considerable attention due to its
potential to circumvent the “von Neumann bottleneck” and mimic human brain activity in …
potential to circumvent the “von Neumann bottleneck” and mimic human brain activity in …
PCMO RRAM for integrate-and-fire neuron in spiking neural networks
S Lashkare, S Chouhan, T Chavan… - IEEE Electron …, 2018 - ieeexplore.ieee.org
Resistance random access memories (RRAM) or memristors with an analog change of
conductance are widely explored as an artificial synapse, eg, Pr 0.7 Ca 0.3 MnO 3 (PCMO) …
conductance are widely explored as an artificial synapse, eg, Pr 0.7 Ca 0.3 MnO 3 (PCMO) …
Memristive Synapses for Brain‐Inspired Computing
J Wang, F Zhuge - Advanced Materials Technologies, 2019 - Wiley Online Library
Although the structure and function of the human brain are still far from being fully
understood, brain‐inspired computing architectures mainly consisting of artificial neurons …
understood, brain‐inspired computing architectures mainly consisting of artificial neurons …
Memory-inspired spiking hyperdimensional network for robust online learning
Recently, brain-inspired computing models have shown great potential to outperform today's
deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiking …
deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiking …