@InProceedings{Supelec444,
author = {Lucian Alecu and Hervé Frezza-Buet},
title = {{An Empirical Evaluation Framework for Qualifying Dynamic Neural Fields}},
year = {2008},
booktitle = {{Proceedings of the second french conference on Computational Neuroscience, Neurocomp, Marseille}},
pages = {(4 pages)},
month = {October},
editor = {Laurent E. Perrinet and Emmanuel Daucé},
url = {http://www.metz.supelec.fr/~alecu_luc/papers/neurocomp08.pdf},
isbn = {978-2-9532965-0-1},
abstract = {In this paper, the behavior of dynamic neural fields is studied
through the lens of performance. As an alternative to the
currently available analytical instruments, an empirical
evaluation methodology is proposed in order to examine the
dynamic quality of a field. This consists of simulating the
field
through various key scenarios and compare the observed behavior
to an optimal expected one. Some desired effects concerning the
evolution of an ideal field are inspected, and a performance
criterion is defined accordingly. Practically, this approach
implements a generic benchmark framework for qualifying neural
fields, allowing to inspect the evolution of the model in
different key situations. The presented methodology provides a
basis for a methodological evaluation of the computational power
of neural fields, when they serve as a basis of decision
processes. In a such integrated system, our approach allows to
tune the free parameters of the field equation according to the
behavior expected from them.}
}