Results 111 to 120 of about 13,938 (239)
Dopamine-like STDP modulation in nanocomposite memristors
AIP Advances, 2019 The development of memristor-based spiking neuromorphic systems (NS) has been essentially driven by the hope to replicate the extremely high energy efficiency of biological systems.
K. E. Nikiruy +7 more
doaj +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Advanced Intelligent Systems, EarlyView.Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
Bioinspired Crossmodal Tactile Sensory Nerve for High‐Accurate Object Recognition
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.An artificial crossmodal sensory neuron system (ACSNS) that combines a complementary memristor with high‐sensitivity pressure–temperature bimodal sensors, which integrate tactile perception, information storage, and neuromorphic computing. With the aid of machine learning, this ACSNS presents an improved accuracy of 96.67% in recognizing temperatures ...
Delu Chen +8 more
wiley +1 more source
Gradual volatile memristor–based artificial neurons with high uniformity for neuromorphic computing
InfoScience, EarlyView.Schematic of leaky integrate‐and‐fire artificial neurons for MNIST image classification. Abstract Artificial neurons are pivotal for neuromorphic hardware, but the development of compact and uniform devices remains challenging. Conventional volatile memristors suffer from abrupt switching, which hinders spatiotemporal consistency.
Pengtao Li +12 more
wiley +1 more source
Learning and discrimination through STDP in a top-down modulated associative memory
, 2006 This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons.
Mouraud, Anthony, Paugam-Moisy, Hélène
core +4 more sources
BrainGrid Simulation Results: Growth and STDP
, 2021 Snigdha Singh, Michael Stiber
openalex +1 more source
InfoScience, EarlyView.This review first introduces the fundamental concepts of artificial synapses and synaptic plasticity, then discusses the device structures and operation mechanisms of optoelectronic synapses based on two‐dimensional transition metal dichalcogenides, highlights their applications in neuromorphic vision systems and computing, and concludes with key ...
Xiaona Sun +3 more
wiley +1 more source
, 2016 Spike-timing dependent plasticity is a learning mechanism used extensively within neural mod-elling. The learning rule has been shown to allow a neuron to find the onset of a spatio-temporalpattern repeated among its afferents. In this study we attempt to answer the question, what doesthis neuron learn?
openaire +1 more source
MXene‐Based Flexible Memory and Neuromorphic Devices
Small, EarlyView.The unique two‐dimensional structure, excellent electrical conductivity, and diverse surface groups of MXenes have garnered significant attention. Coupled with their exceptional flexibility, MXene‐based devices hold immense potential for flexible memory and neuromorphic systems. This review comprehensively discusses the fundamentals of flexible devices,
Yan Li +13 more
wiley +1 more source
S3TC: Spiking Separated Spatial and Temporal Convolutions with Unsupervised STDP-based Learning for Action Recognition [PDF]
, 2023 Mireille El-Assal +2 more
openalex +1 more source