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Hebbian Learning from Spiking Neural P Systems View

  • Miguel A. Gutiérrez-Naranjo
  • Mario J. Pérez-Jiménez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5391)

Abstract

Spiking neural P systems and artificial neural networks are computational devices which share a biological inspiration based on the flow of information among neurons. In this paper we present a first model for Hebbian learning in the framework of spiking neural P systems by using concepts borrowed from neuroscience and artificial neural network theory.

Keywords

Postsynaptic Neuron System Unit System View Presynaptic Neuron Hebbian Learn 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Miguel A. Gutiérrez-Naranjo
    • 1
  • Mario J. Pérez-Jiménez
    • 1
  1. 1.Research Group on Natural Computing Department of Computer Science and Artificial IntelligenceUniversity of SevillaSevillaSpain

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