Hardware-Amenable Structural Learning for Spike-Based Pattern Classification Using a Simple Model of Active Dendrites

DOI10.1162/NECO_A_00713zbMath1473.68150DBLPjournals/neco/HussainLB15arXiv1411.5881OpenAlexW2004159737WikidataQ50597929 ScholiaQ50597929MaRDI QIDQ5380229

Shihchii Liu, Arindam Basu, Shaista Hussain

Publication date: 4 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1411.5881

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Pattern recognition, speech recognition (68T10)

Uses Software

• UCI-ml

Cites Work

• Unnamed Item
• On the complexity of learning for spiking neurons with temporal coding.
• Point-to-point connectivity between neuromorphic chips using address events
• Information Processing in Dendritic Trees
• Neuromorphic implementation of orientation hypercolumns
• Spiking Neuron Models
• Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics
• Synaptic Dynamics in Analog VLSI

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