Recent theoretical studies have shown that probabilistic spiking can be interpreted as
learning and inference in cortical microcircuits. This interpretation creates new opportunities …

Nanoelectronic devices that mimic the functionality of synapses are a crucial requirement for
performing cortical simulations of the brain. In this work, we propose a ferromagnet-heavy …

A device based on current-induced spin-orbit torque (SOT) that functions as an electronic
neuron is proposed in this work. The SOT device implements an artificial neuron's …

A neuromorphic chip that combines CMOS analog spiking neurons and memristive
synapses offers a promising solution to brain-inspired computing, as it can provide massive …

Neuromorphic systems that densely integrate CMOS spiking neurons and nano-scale
memristor synapses open a new avenue of brain-inspired computing. Existing silicon …

Neuromorphic computing attempts to emulate the remarkable efficiency of the human brain
in vision, perception and cognition related tasks. Nanoscale devices that offer a direct …

This paper proposes the utilization of factored forms in logic synthesis for memristive
material implication stateful logic. Factored forms have not been explored by previous works …

Ниже пpеäставëена конöепöия pазpаботки нейpокоìпüþтеpов с пpиìенениеì
ìеìpистоpов, оpиентиpованная на боëüøое и о÷ енü боëüøое÷ исëо вы÷ исëитеëüных …

Neuromorphic computing offers an attractive means for processing and learning complex
real-world data. With the emergence of the memristor, the physical realization of cost …

Abstract Spike Timing Dependent Plasticity is one of the synaptic plasticity rules that plays
an important role in learning and memory in the brain. There are two rules to describe STDP; …