Skip to main content
Article thumbnail
Location of Repository

An Empirical Evaluation Framework for Qualifying Dynamic Neural Fields, in "Deuxième conférence française de Neurosciences Computationnelles, "Neurocomp08

By Lucian Alecu and Hervé Frezza-buet


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. KEY WORDS dynamic neural fields, empirical evaluation

Year: 2013
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • http://hal.archives-ouvertes.f... (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.