Neuromorphic electronics draw attention as innovative approaches that facilitate hardware
implementation of next‐generation artificial intelligent system including neuromorphic in …

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

An electro-optical modulation synaptic device is proposed; it can emulate both brain-like
processing and nervous perception functions by using a special nanoparticle-based …

Conventional von Neumann architecture is insufficient in establishing artificial intelligence
(AI) in terms of energy efficiency, computing in memory and dynamic learning. Delightedly …

Brain-inspired neuromorphic computing, featured by parallel computing, is considered as
one of the most energy-efficient and time-saving architectures for massive data computing …

An all-in-one artificial synapse integrating central nervous and sensory nervous functions
utilizing low-dimensional metal-oxide heterojunction is demonstrated in this work. With an …

Brain-inspired electronics represent a promising paradigm to resolve the energy and time
bottlenecks in conventional digital machines. Recent advances have spanned both …

The practical application of optoelectronic artificial synapses in neuromorphic visual systems
is still hindered by their limited functionality, reliability and the challenge of mass production …

Emerging brain-inspired neuromorphic computing systems have become a potential
candidate for overcoming the von Neuman bottleneck that limits the performance of most …

The typically nonlinear and asymmetric response of synaptic memristors to positive and
negative electrical pulses makes the realization of accurate deep neural networks very …