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Estimation of Autoregressive Parameters from Noisy Observations Using Iterated Covariance Updates
Estimating the parameters of the autoregressive (AR) random process is a problem that has been well-studied. In many applications, only noisy measurements of AR process are available. The effect of the additive noise is that the system can be modeled as an AR model with colored noise, even when the...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517090/ https://www.ncbi.nlm.nih.gov/pubmed/33286345 http://dx.doi.org/10.3390/e22050572 |