Stochastic time-frequency dictionaries for matching pursuit

Authors:
P.J. Durka;D. Ircha;K.J. Blinowska
Affiliations:
Lab. for Med. Phys., Warsaw Univ.;-;-
Venue:
IEEE Transactions on Signal Processing
Year:
2001

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Abstract

Analyzing large amounts of sleep electroencephalogram (EEG) data by means of the matching pursuit (MP) algorithm, we encountered a statistical bias of the decomposition, resulting from the structure of the applied dictionary. As a solution, we propose stochastic dictionaries, where the parameters of the dictionary's waveforms are randomized before each decomposition. The MP algorithm was modified for this purpose and tuned for maximum time-frequency resolution. Examples of applications of the new method include parameterization of EEG structures and time-frequency representation of signals with changing frequency