Neuromorphic computing could address the inherent limitations of conventional silicon
technology in dedicated machine learning applications. Recent work on silicon-based …

This comprehensive review summarizes state of the art, challenges, and prospects of the
neuro-inspired computing with emerging nonvolatile memory devices. First, we discuss the …

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 …

Neuromorphic computers comprised of artificial neurons and synapses could provide a
more efficient approach to implementing neural network algorithms than traditional …

Neuromorphic computing systems, which use electronic synapses and neurons, could
overcome the energy and throughput limitations of today's computing architectures …

Neuromorphic computing has emerged as a promising avenue towards building the next
generation of intelligent computing systems. It has been proposed that memristive devices …

Electronic synaptic devices are important building blocks for neuromorphic computational
systems that can go beyond the constraints of von Neumann architecture. Although two …

Neuromorphic computing represents an innovative technology that can perform intelligent
and energy‐efficient computation, whereas construction of neuromorphic systems requires …

Human eyes undertake the majority of information assimilation for learning and memory.
Transduction of the color and intensity of the incident light into neural signals is the main …

Memristor, based on the principle of biological synapse, is recognized as one of the key
devices in confronting the bottleneck of classical von Neumann computers. However …