Analysis of the ReSuMe Learning Process For Spiking Neural Networks

Authors:
Filip Ponulak
Affiliations:
Institute of Control and Information Engineering Poznań, University of Technology, ul. Piotrowo 3a, 60-965 Poznań, Poland
Venue:
International Journal of Applied Mathematics and Computer Science - Special Section: Selected Topics in Biological Cybernetics, Special Editors: Andrzej Kasiński and Filip Ponulak
Year:
2008

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Abstract

In this paper we perform an analysis of the learning process with the ReSuMe method and spiking neural networks (Ponulak, 2005; Ponulak, 2006b). We investigate how the particular parameters of the learning algorithm affect the process of learning. We consider the issue of speeding up the adaptation process, while maintaining the stability of the optimal solution. This is an important issue in many real-life tasks where the neural networks are applied and where the fast learning convergence is highly desirable.