With their working mechanisms based on ion migration, the switching dynamics and
electrical behaviour of memristive devices resemble those of synapses and neurons, making …

Synaptic devices, including synaptic memristor and synaptic transistor, are emerging
nanoelectronic devices, which are expected to subvert traditional data storage and …

Memristors and memristor crossbar arrays have been widely studied for neuromorphic and
other in-memory computing applications. To achieve optimal system performance, however …

Neuromorphic networks of artificial neurons and synapses can solve computationally hard
problems with energy efficiencies unattainable for von Neumann architectures. For image …

A neuromorphic computing system may be able to learn and perform a task on its own by
interacting with its surroundings. Combining such a chip with complementary metal–oxide …

Sparse representation of information provides a powerful means to perform feature
extraction on high-dimensional data and is of broad interest for applications in signal …

The intrinsic variability of switching behavior in memristors has been a major obstacle to
their adoption as the next generation of universal memory. On the other hand, this natural …

Despite much progress in semiconductor integrated circuit technology, the extreme
complexity of the human cerebral cortex, with its approximately 1014 synapses, makes the …

This review article attempts to provide a comprehensive review of the recent progress in the
so-called resistive random access memories (RRAMs). First, a brief introduction is presented …

Memristors are passive components with a varying resistance that depends on the previous
voltage applied across the device. While memristors are naturally used as memory …