Stochastic time-frequency dictionaries for matching pursuit
- 1 March 2001
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Signal Processing
- Vol. 49 (3) , 507-510
- https://doi.org/10.1109/78.905866
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.Keywords
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