A tutorial overview of modern spectral estimation

A summary of several modern spectral estimation methods is presented. Most of the methods can be explained in the context of parametric time-series modeling. A few methods involve nonparametric treatment. The techniques discussed include classical spectral estimation, autoregressive (maximum entropy), ARMA (autoregressive moving average), Prony, maximum-likelihood, Pisarenko, and MUSIC methods. Many of the techniques have fast computational algorithms, making them viable for real-time applications. The tutorial concludes with a commentary concerning current spectral estimation research.<
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