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

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3 Author(s)
Roessgen, M. ; Signal Process. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia ; Deriche, M. ; Boashash, B.

The 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

Published in:

Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on

Date of Conference:

1-3 Nov 1993

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