A non-volatile locally active memristor is a promising candidate for neuromorphic computing
based on artificial synapses and neurons, due to its high-speed switching, strong scalability …

Analog circuit implementation of neuron model is an essential category of neuromorphic
circuit since it can reproduce neuron firing patterns and assist in exploring neuron-based …

Nanoscale S‐type NbOx locally active memristors (LAMs) open up new opportunities in the
brain‐inspired neuromorphic computing. Simple yet accurate models for these memristors …

Conventional CMOS technology is slowly approaching its physical limitations and
researchers are increasingly utilizing nanotechnology to both extend CMOS capabilities and …

Memristors have been rediscovered recently and then gained increasing attentions. Their
unique properties, such as high density, nonvolatility, and recording historic behavior of …

Spike-time-dependent plasticity (STDP) represents an essential learning rule found in
biological synapses and is recommended for replication in neuromorphic electronic …

Conventional CMOS technology is slowly approaching its physical limitations and
researchers are increasingly utilizing nanotechnology to both extend CMOS capabilities and …

The memristor is a promising candidate to implement high-density memory and
neuromorphic computing. Based on the characteristic retention time, memristors are …

Neuromorphic hardware is a system with massive potential to enable efficient computing by
mimicking the human brain. The novel system processes information using neuron spikes …

A synaptic structure with memristor state initialization function and a neuronal circuit with
structural variability are presented in this article. In contrast to the popular use of voltage as a …