A memristor is a resistive device with an inherent memory. The theoretical concept of a
memristor was connected to physically measured devices in 2008 and since then there has …

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …

An optoelectronic synapse having a multispectral color-discriminating ability is an essential
prerequisite to emulate the human retina for realizing a neuromorphic visual system. Several …

Although several types of architecture combining memory cells and transistors have been
used to demonstrate artificial synaptic arrays, they usually present limited scalability and …

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

The progress in the field of neural computation hinges on the use of hardware more efficient
than the conventional microprocessors. Recent works have shown that mixed-signal …

Analog hardware accelerators, which perform computation within a dense memory array,
have the potential to overcome the major bottlenecks faced by digital hardware for data …

In this article, we review the existing analog resistive switching memory (RSM) devices and
their hardware technologies for in-memory learning, as well as their challenges and …

Historically, memory technologies have been evaluated based on their storage density, cost,
and latencies. Beyond these metrics, the need to enable smarter and intelligent computing …

Memristor-based synaptic network has been widely investigated and applied to
neuromorphic computing systems for the fast computation and low design cost. As …