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Adaptive Detection and Removal of Non-Gaussian Spikes from Gaussian Data
February 1982 (vol. 4 no. 2)
pp. 132-136
R. E. Boucher, Bedford Research Associates, Bedford, MA 01730.
J. P. Noonan, Bedford Research Associates, Bedford, MA 01730.
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.
Citation:
R. E. Boucher, J. P. Noonan, "Adaptive Detection and Removal of Non-Gaussian Spikes from Gaussian Data," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 2, pp. 132-136, Feb. 1982, doi:10.1109/TPAMI.1982.4767218
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