ICA-based EEG spatio-temporal dipole source localization: A model study

Ling Zou, Shan An Zhu, Bin He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we examine the performance of an Independent Component Analysis (ICA) based dipole localization approach to localize multiple source dipoles under noisy environment. Uncorrelated noise of up to 40% was added to scalp EEG signals. The performance of the ICA-based algorithm is compared with the conventional localization procedure using Simplex method. The present simulation results indicate the robustness of the ICA-based approach in localizing multiple dipoles of independent sources.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Networks - ISNN 2006
Subtitle of host publicationThird International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III
PublisherSpringer Verlag
Pages566-572
Number of pages7
ISBN (Print)3540344829, 9783540344827
DOIs
StatePublished - Jan 1 2006
Event3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks - Chengdu, China
Duration: May 28 2006Jun 1 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3973 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks
Country/TerritoryChina
CityChengdu
Period5/28/066/1/06

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