Learning algorithm for spiking neural networks

Authors:
Hesham H. Amin;Robert H. Fujii
Affiliations:
The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan;The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

Citing 7
Cited 0

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Abstract

Spiking Neural Networks (SNNs) use inter-spike time coding to process input data. In this paper, a new learning algorithm for SNNs that uses the inter-spike times within a spike train is introduced. The learning algorithm utilizes the spatio-temporal pattern produced by the spike train input mapping unit and adjusts synaptic weights during learning. The approach was applied to classification problems.