ITEM METADATA RECORD
Title: Kernel-based topographic map formation achieved with normalized Gaussian competition
Authors: Van Hulle, Marc # ×
Issue Date: 2002
Host Document: Proceedings pages:169-178
Conference: IEEE Workshop on Neural Networks for Signal Processing location:Martigny, Valais, Switzerland date:4-6 September 2002
Abstract: A new learning algorithm for kernel-based topographic map formation is introduced. The kernels are Gaussians, and their centers and ranges individually adapted so as to yield an equiprobabilistic topographic map. The converged map also generates a heteroscedastic Gaussian mixture model of the input density. This is verified for both synthetic and real-world examples, and compared with other algorithms for kernel-based topographic map formation.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Research Group Neurophysiology
× corresponding author
# (joint) last author

Files in This Item:

There are no files associated with this item.

Request a copy

 




All items in Lirias are protected by copyright, with all rights reserved.

© Web of science