Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Using memristor crossbar arrays to accelerate computations is a promising approach to
efficiently implement algorithms in deep neural networks. Early demonstrations, however …

Neural networks have enabled applications in artificial intelligence through machine
learning, and neuromorphic computing. Software implementations of neural networks on …

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

Recent progress in artificial intelligence is largely attributed to the rapid development of
machine learning, especially in the algorithm and neural network models. However, it is the …

It has long been known that photonic communication can alleviate the data movement
bottlenecks that plague conventional microelectronic processors. More recently, there has …

Neuro-inspired architectures based on synaptic memory arrays have been proposed for on-
chip acceleration of weighted sum and weight update in machine/deep learning algorithms …