The emergence of memristors with potential applications in data storage and artificial
intelligence has attracted wide attentions. Memristors are assembled in crossbar arrays with …

Being capable of dealing with both electrical signals and light, artificial optoelectronic
synapses are of great importance for neuromorphic computing and are receiving a …

Recent years have witnessed a surge of interest in learning representations of graph-
structured data, with applications from social networks to drug discovery. However, graph …

Mechanoreceptors endow humans with the sense of touch by translating the external stimuli
into coded spikes, inspiring the rise of artificial mechanoreceptor systems. However, to …

Neuromorphic computing targets the hardware embodiment of neural network, and device
implementation of individual neuron and synapse has attracted considerable attention. The …

As key components of the human brain's neural network, synapses and neurons are
important processing units that enable highly complex neuromorphic systems. Spiking …

As semiconductor technology enters the more than Moore era, there exists an apparent
contradiction between the rapidly growing demands for data processing and the visible …

Artificial neuronal devices are critical building blocks of neuromorphic computing systems
and currently the subject of intense research motivated by application needs from new …

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

Spiking neural networks (SNNs) are biologically plausible and computationally powerful.
The current computing systems based on the von Neumann architecture are almost the …