Approximating the Time-Frequency Representation of Biosignals with Chirplets. (2010) - Talakoub Talakoub, Omid Omid; Cui Cui, Jie Jie; Wong Wong, Willy Willy
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.