Extraction of Intrawave Signals Using Sparse Time-Frequency Representation Method

Peyman Tavallali Caltech Thomas Y. Hou Caltech Zuoqiang Shi Tsinghua University

Numerical Analysis and Scientific Computing mathscidoc:1709.25010

SIAM: Multiscale Modeling & Simulation, 12, (4), 1458-1493, 2014
Analysis and extraction of strongly frequency modulated signals have been a challenging problem for Adaptive Data Analysis methods; e.g., Empirical Mode Decomposition (EMD) [13]. 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 (STFR) methods [8, 7]. 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.
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@inproceedings{peyman2014extraction,
  title={Extraction of Intrawave Signals Using Sparse Time-Frequency Representation Method},
  author={Peyman Tavallali, Thomas Y. Hou, and Zuoqiang Shi},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170927101230002290829},
  booktitle={SIAM: Multiscale Modeling & Simulation},
  volume={12},
  number={4},
  pages={1458-1493},
  year={2014},
}
Peyman Tavallali, Thomas Y. Hou, and Zuoqiang Shi. Extraction of Intrawave Signals Using Sparse Time-Frequency Representation Method. 2014. Vol. 12. In SIAM: Multiscale Modeling & Simulation. pp.1458-1493. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170927101230002290829.
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