Spike Based Learning | List of Frontiers open access articles

Original Research

Published on 02 Oct 2015

Implementation of a spike-based perceptron learning rule using TiO2−x memristors

in Neuromorphic Engineering

Hesham Mostafa
Ali Khiat
Alexander Serb
Christian G. Mayr
Giacomo Indiveri
Themis Prodromakis

Frontiers in Neuroscience

doi 10.3389/fnins.2015.00357

8,522 views
40 citations

Original Research

Published on 28 Jun 2017

An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data

in Neuromorphic Engineering

Evangelos Stromatias
Miguel Soto
Teresa Serrano-Gotarredona
Bernabé Linares-Barranco

Frontiers in Neuroscience

doi 10.3389/fnins.2017.00350

22,487 views
99 citations

Original Research

Published on 28 Feb 2020

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures

in Neuromorphic Engineering

Chankyu Lee
Syed Shakib Sarwar
Priyadarshini Panda
Gopalakrishnan Srinivasan
Kaushik Roy

Frontiers in Neuroscience

doi 10.3389/fnins.2020.00119

35,354 views
397 citations

Original Research

Published on 18 Apr 2022

SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory

in Neuromorphic Engineering

Shuangming Yang
Tian Gao
Jiang Wang
Bin Deng
Mostafa Rahimi Azghadi
Tao Lei
Bernabe Linares-Barranco

Frontiers in Neuroscience

doi 10.3389/fnins.2022.850945

8,118 views
81 citations

Original Research

Published on 31 Mar 2016

Multiclass Classification by Adaptive Network of Dendritic Neurons with Binary Synapses Using Structural Plasticity

in Neuromorphic Engineering

Shaista Hussain
Arindam Basu

Frontiers in Neuroscience

doi 10.3389/fnins.2016.00113

5,417 views
12 citations

Original Research

Published on 21 Apr 2023

Boost event-driven tactile learning with location spiking neurons

in Neuromorphic Engineering

Peng Kang
Srutarshi Banerjee
Henry Chopp
Aggelos Katsaggelos
Oliver Cossairt

Frontiers in Neuroscience

doi 10.3389/fnins.2023.1127537

3,949 views
14 citations

Articles

Implementation of a spike-based perceptron learning rule using TiO2−x memristors

An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures

SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory

Multiclass Classification by Adaptive Network of Dendritic Neurons with Binary Synapses Using Structural Plasticity

Boost event-driven tactile learning with location spiking neurons