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Application-driven parameter tuning methodology for dynamic neural field equations

Lucian Alecu 1, 2 Hervé Frezza-Buet 1
2 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In this paper, a method is introduced in order to qualify the performance of dynamic neural fields (DNF). The method is applied to Amari's DNF equations, in order to drive the tuning of its free parameters. An original evaluation procedure is presented, and then applied to some input evolution scenarios. Such scenarios define an applicative context, for which the parameters with the lowest evaluation are optimal.
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https://hal-supelec.archives-ouvertes.fr/hal-00439332
Contributor : Sébastien van Luchene <>
Submitted on : Monday, December 7, 2009 - 12:26:38 PM
Last modification on : Tuesday, April 21, 2020 - 10:58:27 AM

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Lucian Alecu, Hervé Frezza-Buet. Application-driven parameter tuning methodology for dynamic neural field equations. 16th International Conference on Neural Information Processing - ICONIP 2009, Dec 2009, Bangkok, Thailand. pp.135-142, ⟨10.1007/978-3-642-10677-4_15⟩. ⟨hal-00439332⟩

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