Approximating the time-frequency representation of biosignals with chirplets

Authors:
Omid Talakoub;Jie Cui;Willy Wong
Affiliations:
Department of Electrical and Computer Engineering, University of Toronto, On, Canada;Department of Electrical and Computer Engineering, University of Toronto, On, Canada;Department of Electrical and Computer Engineering, University of Toronto, On, Canada
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on applications of time-frequency signal processing in wireless communications and bioengineering
Year:
2010

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Abstract

A new member of the Cohen's class time-frequency distribution is proposed. The kernel function is determined adaptively based on the signal of interest. The kernel preserves the chirp-like components while removing interference terms generated due to the quadratic characteristic of Wigner-Ville distribution. This approach is based on the chirplet as an underlying model of biomedical signals. We illustrate the method using a number of common biological signals including echo-location and evoked potential signals. Finally, the results are compared with other techniques including chirplet decomposition via matching pursuit and the Choi-Williams distribution function.