Analysis of the ReSuMe learning process for spiking neural networks

Filip Ponulak

International Journal of Applied Mathematics and Computer Science (2008)

  • Volume: 18, Issue: 2, page 117-127
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Filip Ponulak. "Analysis of the ReSuMe learning process for spiking neural networks." International Journal of Applied Mathematics and Computer Science 18.2 (2008): 117-127. <http://eudml.org/doc/207870>.

@article{FilipPonulak2008,
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.},
author = {Filip Ponulak},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {supervised learning; spiking neural networks; parametric analysis; learning window},
language = {eng},
number = {2},
pages = {117-127},
title = {Analysis of the ReSuMe learning process for spiking neural networks},
url = {http://eudml.org/doc/207870},
volume = {18},
year = {2008},
}

TY - JOUR
AU - Filip Ponulak
TI - Analysis of the ReSuMe learning process for spiking neural networks
JO - International Journal of Applied Mathematics and Computer Science
PY - 2008
VL - 18
IS - 2
SP - 117
EP - 127
AB - 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.
LA - eng
KW - supervised learning; spiking neural networks; parametric analysis; learning window
UR - http://eudml.org/doc/207870
ER -

References

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