HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Parameterized normalization : application to wavelet networks

Richard Baron 1 Bernard Girau 2
2 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Normalization is studied in the case of wavelet networks, and we derive a dynamic interpretation of its influence, which can be extended to several neural models. We show that data normalization may be simulated and parameterized to avoid data preprocessing, so that the normalization process becomes either tunable or dynamically adaptable. The main benefit of the proposed methods is a big reduction of the time of convergence on a satisfactory classification rate.
Document type :
Conference papers
Complete list of metadata

https://hal.inria.fr/inria-00108033
Contributor : Publications Loria Connect in order to contact the contributor
Submitted on : Thursday, October 19, 2006 - 3:40:17 PM
Last modification on : Thursday, February 3, 2022 - 11:10:29 AM

Identifiers

  • HAL Id : inria-00108033, version 1

Citation

Richard Baron, Bernard Girau. Parameterized normalization : application to wavelet networks. IJCNN, 1998, none, 5 p. ⟨inria-00108033⟩

Share

Metrics

Record views

89