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Information visualization for knowledge extraction in neural networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a user-centred innovative method of knowledge extraction in neural networks is described. This is based on information visualization techniques and tools for artificial and natural neural systems. Two case studies are presented. The first demonstrates the use of various information visualization methods for the identification of neuronal structure (e.g. groups of neurons that fire synchronously) in spiking neural networks. The second study applies similar techniques to the study of embodied cognitive robots in order to identify the complex organization of behaviour in the robot’s neural controller.
Original languageEnglish
Title of host publicationArtificial Neural Networks: Formal Models and Their Applications - ICANN 2005
Pages515-520
Number of pages6
ISBN (Electronic)978-3-540-28756-8
DOIs
Publication statusPublished (in print/issue) - 1 Jan 2005

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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