ITEM METADATA RECORD
Title: The formation of topographic maps that maximize the average mutual information of the output responses to noiseless input signals
Authors: Van Hulle, Marc # ×
Issue Date: 1997
Publisher: M I T PRESS
Series Title: Neural computation vol:9 issue:3 pages:595-606
Abstract: This article introduces an extremely simple and local learning rule for topographic map formation. The rule, called the maximum entropy learning rule (MER), maximizes the unconditional entropy of the map's output for any type of input distribution. The aim of this article is to show that MER is a viable strategy for building topographic maps that maximize the average mutual information of the output responses to noiseless input signals when only input noise and noise-added input signals are available.
ISSN: 0899-7667
Publication status: published
KU Leuven publication type: IT
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