Memristors, promising nanoelectronic devices with in-memory resistive switching behavior
that is assembled with a physically integrated core processing unit (CPU) and memory unit …

The slowing down of transistor scaling and explosive growth for intelligence computing
power emerge as the two driving factors for the study of novel devices and materials to …

Electromagnetic induction plays a vital role in impacting the neuron dynamics, since the
electromagnetic induction is triggered alongside with the complex interaction of membrane …

Most memristor-based neural network circuits consider only a single pattern of
overshadowing or emotion, but the relationship between overshadowing and emotion is …

When taking a memristor as a coupler to connect two memristive systems, the intricate initial
condition-dependent coexisting and synchronous behaviors could be achieved, which have …

Hybrid perovskites have attracted enormous attention in the next generation resistive
switching (RS) memristor for the artificial synapses, owing to their ambipolar charge …

This article introduces a novel model of asymmetric neural networks combined with
fractional difference memristors, which has both theoretical and practical implications in the …

The cellular neural network (CNN) is an implementable solution for fully connected neural
networks. Using nanoscale memristor to realize its nonlinear activation function can simplify …

Capacitive membrane and inductive channels enable the approach of neural activities in
some equivalent neural circuits, and involvement of memristive term and magnetic flux can …

In designing neuromorphic circuits and systems, developing compact and energy-efficient
neuron and synapse circuits is essential for high-performance on-chip neural architectures …