Memristive arrays are a natural fit to implement spiking neural network (SNN) acceleration.
Representing information as digital spiking events can improve noise margins and tolerance …

Memristors show great potential for being integrated into CMOS technology and provide
new approaches for designing computing-in-memory (CIM) systems, brain-inspired …

The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …

Spiking firing patterns and their hardware implementation can assist us in exploring spike-
based applications. The classical Hodgkin–Huxley circuit can generate spiking firing …

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 …

Abstract The famous Hodgkin-Huxley circuit contains two time-varying resistors to describe
the electrophysiological characteristics of sodium and potassium ion channels. But the time …

Neurons, which are made of biological tissue, exhibit cognitive properties that can be
replicated in various material substrates. To create brain-inspired computational artificial …

The vast majority of studies that process and analyze neural signals are conducted on cloud
computing resources, which is often necessary for the demanding requirements of deep …

This paper proposes CMOS synapse and neuron for use in spiking neural networks to
perform cognitive functions in a bio-inspired manner. The proposed synapse can trace the …

This manuscript provides a comprehensive tutorial on the operating principles of a bio-
inspired Cellular Nonlinear Network, leveraging the local activity of NbO x memristors to …