Realizing multi-modal information recognition tasks which can process external information
efficiently and comprehensively is an urgent requirement in the field of artificial intelligence …

The brain has effectively proven a powerful inspiration for the development of computing
architectures in which processing is tightly integrated with memory, communication is event …

Memristors mimic synaptic functions in advanced electronics and image sensors, thereby
enabling brain-inspired neuromorphic computing to overcome the limitations of the von …

Hyperdimensional computing (HDC) is a brain-inspired computational framework that relies
on long hypervectors (HVs) for learning. In HDC, computational operations consist of simple …

Artificial neural networks (ANNs) have gained considerable momentum in the past decade.
Although at first the main task of the ANN paradigm was to tune the connection weights in …

This work reports that synchronization of Mott material-based nanoscale coupled spiking
oscillators can be drastically different from that in conventional harmonic oscillators. We …

Recently, memristors with brain-like synaptic behavior have attracted widespread attention,
offering unprecedented opportunities for constructing future artificial intelligent bio-inspired …

Neural Networks (NNs) provide an effective solution in numerous application domains,
including autonomous driving and medical applications. Nevertheless, NN predictions can …

In recent years, memristors have successfully demonstrated their significant potential in
artificial neural networks (ANNs) and neuromorphic computing. Nonetheless, ANNs …

The implementation of inference (ie, computing posterior probabilities) in Bayesian networks
using a conventional computing paradigm turns out to be inefficient in terms of energy, time …