Emerging memristive artificial synapses and neurons for energy‐efficient neuromorphic computing
Memristors have recently attracted significant interest due to their applicability as promising
building blocks of neuromorphic computing and electronic systems. The dynamic …
building blocks of neuromorphic computing and electronic systems. The dynamic …
Progress of materials and devices for neuromorphic vision sensors
The latest developments in bio-inspired neuromorphic vision sensors can be summarized in
3 keywords: smaller, faster, and smarter.(1) Smaller: Devices are becoming more compact …
3 keywords: smaller, faster, and smarter.(1) Smaller: Devices are becoming more compact …
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
Memristors with tunable resistance states are emerging building blocks of artificial neural
networks. However, in situ learning on a large-scale multiple-layer memristor network has …
networks. However, in situ learning on a large-scale multiple-layer memristor network has …
The next generation of deep learning hardware: Analog computing
Initially developed for gaming and 3-D rendering, graphics processing units (GPUs) were
recognized to be a good fit to accelerate deep learning training. Its simple mathematical …
recognized to be a good fit to accelerate deep learning training. Its simple mathematical …
Complementary metal‐oxide semiconductor and memristive hardware for neuromorphic computing
M Rahimi Azghadi, YC Chen… - Advanced Intelligent …, 2020 - Wiley Online Library
The ever‐increasing processing power demands of digital computers cannot continue to be
fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing …
fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing …
Synapse‐like organic thin film memristors
Exploring new type of synapse–like electronic devices with fusion of computing and memory
is a promising strategy to fundamentally approach to intelligent machines. Herein, organic …
is a promising strategy to fundamentally approach to intelligent machines. Herein, organic …
Toward a Reliable Synaptic Simulation Using Al-Doped HfO2 RRAM
The potential in a synaptic simulation for neuromorphic computation has revived the
research interest of resistive random access memory (RRAM). However, novel applications …
research interest of resistive random access memory (RRAM). However, novel applications …
Resistive memory-based analog synapse: The pursuit for linear and symmetric weight update
This article reviews the recent developments in a type of random access memory (RAM)
called resistive RAM (RRAM) for the analog synapse, which is an important building block …
called resistive RAM (RRAM) for the analog synapse, which is an important building block …
Signal and noise extraction from analog memory elements for neuromorphic computing
Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively
parallel and highly energy-efficient neuromorphic computing systems. The key requirements …
parallel and highly energy-efficient neuromorphic computing systems. The key requirements …
Neuromorphic synapses with high switching uniformity and multilevel memory storage enabled through a Hf-Al-O alloy for artificial intelligence
Due to their high data-storage capability, oxide-based memristors with controllable
conductance properties have attracted great interest in electronic devices for high …
conductance properties have attracted great interest in electronic devices for high …