Extraction of Intrawave Signals Using the Sparse Time-Frequency Representation Method

Analysis and extraction of strongly frequency modulated signals have been a challenging problem for adaptive data analysis methods, e.g., empirical mode decomposition [N.E. Huang et al., R. Soc. Lond. Proc. Ser. A Math. Phys. Eng. Sci., 454 (1998), pp. 903–995]. In fact, many of the Newtonian dynamical systems, including conservative mechanical systems, are sources of signals with low to strong levels of frequency modulation. Analysis of such signals is an important issue in system identification problems. In this paper, we present a novel method to accurately extract intrawave signals. This method is a descendant of sparse time-frequency representation methods [T.Y. Hou and Z. Shi, Appl. Comput. Harmon. Anal., 35 (2013), pp. 284–308, T.Y. Hou and Z. Shi, Adv. Adapt. Data Anal., 3 (2011), pp. 1–28]. We will present numerical examples to show the performance of this new algorithm. Theoretical analysis of convergence of the algorithm is also presented as a support for the method. We will show that the algorithm is stable to noise perturbation as well.