By Topic

Time-variable filtering of multichannel signals using multiple windows coherence and the Weyl transform

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wahlberg, Patrik ; Dept. of Appl. Electron., Lund Univ., Sweden ; Hansson, M.

This paper deals with noise suppression in multichannel measurements, using a certain signal model but without assuming stationarity of the signals involved. This enables application to signals whose spectral characteristics are time-variable. The novelty consists of an algorithm for obtaining an approximation of the Wiener filter for each channel. The filters are computed using the Weyl transform and estimates of the time-frequency coherence function between all channel pairs. Time-frequency coherence functions are estimated using the multiple window method, adapted to peaked spectra. Our method is evaluated on EEG signals from epileptic seizure onsets which are measured at multiple locations on the scalp. The filtered signals give improved time-frequency representations, and also the resulting filters studied in the time-frequency domain reveal otherwise not visible signal features

Published in:

Sensor Array and Multichannel Signal Processing Workshop. 2000. Proceedings of the 2000 IEEE

Date of Conference: