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A neural network for learning the meaning of objects and words from a featural representation

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Publication:889400
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DOI10.1016/j.neunet.2014.11.009zbMath1368.92017OpenAlexW1967675628WikidataQ38418073 ScholiaQ38418073MaRDI QIDQ889400

Cristiano Cuppini, Elisa Magosso, Mauro Ursino

Publication date: 6 November 2015

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

Full work available at URL: https://doi.org/10.1016/j.neunet.2014.11.009


zbMATH Keywords

category formationconceptual representationdominant featuresHebb rulelexical memorysemantic memory


Mathematics Subject Classification ID

Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20)


Related Items (2)

Neurocomputational approaches to modelling multisensory integration in the brain: a review ⋮ An unsupervised parameter learning model for RVFL neural network



Cites Work

  • Unnamed Item
  • A theory for the acquisition and loss of neuron specificity in visual cortex
  • Modeling Brain Function
  • Mean-field analysis of neuronal spike dynamics
  • Neurons with graded response have collective computational properties like those of two-state neurons.


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