Evoked potentials estimation by using higher order adaptive neural network filter

Bor-Shyh Lin, Bor Shing Lin, Fok Ching Chong

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

1 Scopus citations

Abstract

Evoked potentials are usually embedded in the ongoing electroencephalogram with a very low signal-to-noise ratio. The neural network filtering technique which has the advantage of complex mapping is one of the applicable methods for evoked potentials estimation. The back-propagation algorithm based on second order statistics is commonly used to adapt neural network filters. However it is easily influenced by additive Gaussian noise. In this study, a neural network filter with a modified back-propagation algorithm for higher order statistics was proposed. With higher-order statistics technique, additive Gaussian noise is suppressed to improve the performance of evoked potentials estimation.

Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages1139-1141
Number of pages3
DOIs
StatePublished - 1 Dec 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 1 Sep 20054 Sep 2005

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Conference

Conference2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
CountryChina
CityShanghai
Period1/09/054/09/05

Keywords

  • Back-propagation algorithm
  • Evoked potentials
  • Higher order statistics
  • Neural network filter

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    Lin, B-S., Lin, B. S., & Chong, F. C. (2005). Evoked potentials estimation by using higher order adaptive neural network filter. In Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 (pp. 1139-1141). [1616622] (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings; Vol. 7 VOLS). https://doi.org/10.1109/IEMBS.2005.1616622