Hebbian Learning from Spiking Neural P Systems View

Authors:
Miguel A. Gutiérrez-Naranjo;Mario J. Pérez-Jiménez
Affiliations:
Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Sevilla, Sevilla, Spain 41012;Research Group on Natural Computing Department of Computer Science and Artificial Intelligence, University of Sevilla, Sevilla, Spain 41012
Venue:
Membrane Computing
Year:
2009

Citing 3
Cited 2

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Spiking Neuron Models: An Introduction
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Fundamenta Informaticae

Spiking Neural P Systems with Weighted Synapses

Neural Processing Letters
On structures and behaviors of spiking neural p systems and petri nets

CMC'12 Proceedings of the 13th international conference on Membrane Computing

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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.