Corpus ID: 234741799

Data-driven Algorithms for signal processing with rational functions

@article{Wilber2021DatadrivenAF,
  title={Data-driven Algorithms for signal processing with rational functions},
  author={Heather Wilber and Anil Damle and Alex Townsend},
  journal={ArXiv},
  year={2021},
  volume={abs/2105.07324}
}
Rational approximation schemes for reconstructing signals from samples with poorly separated spectral content are described. These methods are automatic and adaptive, requiring no tuning or manual parameter selection. Collectively, they form a framework for fitting trigonometric rational models to data that is robust to various forms of corruption, including additive Gaussian noise, perturbed sampling grids, and missing data. Our approach combines a variant of Prony’s method with a modified… Expand

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