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A kernel based system for the estimation of non-stationary signals

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2 Author(s)
Jemili, K. ; Dept. of Electr. Eng., Dayton Univ., OH, USA ; Westerkamp, John J.

A new signal estimation technique is introduced for highly non-stationary signals. The system uses the wavelet transform to extract time-frequency components of the signal plus noise, followed by a radial basis function neural network that adaptively estimates the underlying signal. The method is applied to the visual evoked potential (EP) signal, which is a transient signal corrupted by the ongoing electroencephalogram (EEG) noise, with a signal-to-noise ratio often less than -6 dB. The proposed system gives good time-varying estimates of the EP, while suppressing the on-going EEG

Published in:

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on  (Volume:5 )

Date of Conference:

9-12 May 1995

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