# Maximum Entropy Spectral Analysis: a case study

@inproceedings{Martini2021MaximumES, title={Maximum Entropy Spectral Analysis: a case study}, author={A. Martini and S. Schmidt and W. D. Pozzo}, year={2021} }

The Maximum Entropy Spectral Analysis (MESA) method, developed by Burg, provides a powerful tool to perform spectral estimation of a time-series. The method relies on a Jaynes’ maximum entropy principle and provides the means of inferring the spectrum of a stochastic process in terms of the coefficients of some autoregressive process AR(p) of order p. A closed form recursive solution provides an estimate of the autoregressive coefficients as well as of the order p of the process. We provide a… Expand

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