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Application-Driven Parameter Tuning Methodology for Dynamic Neural Field Equations

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Neural Information Processing (ICONIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5863))

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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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© 2009 Springer-Verlag Berlin Heidelberg

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Alecu, L., Frezza-Buet, H. (2009). Application-Driven Parameter Tuning Methodology for Dynamic Neural Field Equations. In: Leung, C.S., Lee, M., Chan, J.H. (eds) Neural Information Processing. ICONIP 2009. Lecture Notes in Computer Science, vol 5863. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10677-4_15

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  • DOI: https://doi.org/10.1007/978-3-642-10677-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10676-7

  • Online ISBN: 978-3-642-10677-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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