publication . Article . Other literature type . 2012

SPAN: spike pattern association neuron for learning spatio-temporal sequences

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N;
Open Access English
  • Published: 01 Jan 2012
  • Publisher: World Scientific Publishing
  • Country: Switzerland
Abstract
Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations ca...
Subjects
arXiv: Quantitative Biology::Neurons and Cognition
free text keywords: Institute of Neuroinformatics, 570 Life sciences; biology
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