Stochastic time-frequency dictionaries for matching pursuit

Author

Durka, Piotr J. ; Ircha, Dobieslaw ; Blinowska, Katarzyna J.

Author_Institution

Lab. for Med. Phys., Warsaw Univ., Poland

Volume

49

Issue

3

fYear

2001

fDate

3/1/2001 12:00:00 AM

Firstpage

507

Lastpage

510

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

electroencephalography; medical signal processing; signal representation; signal resolution; statistical analysis; stochastic processes; time-frequency analysis; EEG data; brain; decomposition; matching pursuit algorithm; maximum time-frequency resolution; signal representation; sleep electroencephalogram data; statistical bias; stochastic time-frequency dictionaries; time-frequency representation; waveforms; Dictionaries; Electroencephalography; Matching pursuit algorithms; Pursuit algorithms; Sampling methods; Signal resolution; Sleep; Stochastic processes; Time frequency analysis; Transient analysis;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.905866

Filename

905866