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Comparative study of spectral estimation techniques for noisy non-stationary signals with application to EEG data

  • Queensland University of Technology

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

4 Scopus citations

Abstract

This paper considers the problem of spectral estimation of noisy non-stationary signals with application to electroencephalogram (EEG) data. Four well known methods for estimating the time-varying spectrum of a non-stationary signal are first reviewed and their performance compared. These methods which work well when the signal-to-noise ratio (SNR) is high, are shown to fail with varying degrees as SNR decreases. A technique for preprocessing noisy EEG data called time-frequency peak filtering (TFPF) is then presented and used to process EEG signals whose spectral content are highly non-stationary and difficult to model. It is shown that marked improvement in spectral estimates result after using the TFPF method.

Original languageEnglish
Title of host publicationConference Record of the Asilomar Conference of Signals, Systems & Computers
PublisherPubl by IEEE
Pages1157-1161
Number of pages5
ISBN (Print)0818641207
StatePublished - 1993
Externally publishedYes
EventProceedings of the 27th Asilomar Conference on Signals, Systems & Computers - Pacific Grove, CA, USA
Duration: 1 Nov 19933 Nov 1993

Publication series

NameConference Record of the Asilomar Conference of Signals, Systems & Computers
Volume2
ISSN (Print)1058-6393

Conference

ConferenceProceedings of the 27th Asilomar Conference on Signals, Systems & Computers
CityPacific Grove, CA, USA
Period1/11/933/11/93

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