Sound classification and function approximation using 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:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Year:
2005

Citing 5
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Abstract

The capabilities and robustness of a new spiking neural network (SNN) learning algorithm are demonstrated with sound classification and function approximation applications. The proposed SNN learning algorithm and the radial basis function (RBF) learning method for function approximation are compared. The complexity of the learning algorithm is analyzed.