Optoelectronic memristors (OMs) have emerged as a promising optoelectronic
Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic …

Flexible neuromorphic electronics that emulate biological neuronal systems constitute a
promising candidate for next‐generation wearable computing, soft robotics, and …

The priority of synaptic device researches has been given to prove the device potential for
the emulation of synaptic dynamics and not to functionalize further synaptic devices for more …

In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

Neuromorphic computing can potentially solve the von Neumann bottleneck of current
mainstream computing because it excels at self‐adaptive learning and highly parallel …

In the brain, most synapses are formed on minute protrusions known as dendritic spines.
Unlike their artificial intelligence counterparts, spines are not merely tuneable memory …

The search for new “neuromorphic computing” architectures that mimic the brain's approach
to simultaneous processing and storage of information is intense. Because, in real brains …

Neuromorphic computing holds promise for building next‐generation intelligent systems in a
more energy‐efficient way than the conventional von Neumann computing architecture …

This paper will review emerging non-volatile memory (NVM) technologies, with the focus on
phase change memory (PCM), spin-transfer-torque random-access-memory (STTRAM) …

The synapse is the focus of experimental research and theory on the cellular mechanisms of
nervous system plasticity and learning, but recent research is expanding the consideration …