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Memorias de investigación
Communications at congresses:
On the Biological Plausibility of Artificial Metaplasticity
Year:2011
Research Areas
  • Engineering
Information
Abstract
The training algorithm studied in this paper is inspired by the biological metaplasticity property of neurons. Tested on different multidisciplinary applications, it achieves a more efficient training and improves Artificial Neural Network Performance. The algorithm has been recently proposed for Artificial Neural Networks in general, although for the purpose of discussing its biological plausibility, a Multilayer Perceptron has been used. During the training phase, the artificial metaplasticity multilayer perceptron could be considered a new probabilistic version of the presynaptic rule, as during the training phase the algorithm assigns higher values for updating the weights in the less probable activations than in the ones with higher probability.
International
Si
Congress
IWINAC 2011
960
Place
La Palma, Islas Canarias, España
Reviewers
Si
ISBN/ISSN
0302-9743
10.1007/978-3-642-21344-1_13
Start Date
30/05/2011
End Date
03/06/2011
From page
119
To page
128
Foundations on Natural and Artificial Computation Lecture Notes in Computer Science, 2011, Volume 6686/2011
Participants
  • Autor: Diego Andina De la Fuente (UPM)
  • Autor: Francisco J Ropero-Peláez (Universidad Federal de ABC, Brasil)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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