By Topic

Adaptive Detection and Removal of Non-Gaussian Spikes from Gaussian Data

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)
Boucher, R.E. ; Bedford Research Associates, Bedford, MA 01730. ; Noonan, J.P.

A nonlinear adaptive method is presented for filtering a signal which is corrupted by spikes which take discrete values Mi with probability Pi at random points in time. An unsupervised learning technique is used to estimate the unknown parameters Mi, Pi, and oi. The spikes are then removed using a Bayes classifier. A theoretical and experimental comparison with the MMSE linear filter is presented.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:PAMI-4 ,  Issue: 2 )