Signal polynomial smoothing from correlated interrupted observations based on covariances
✍ Scribed by S. Nakamori; R. Caballero-Águila; A. Hermoso-Carazo; J. D. Jiménez-López; J. Linares-Pérez
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 198 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0170-4214
- DOI
- 10.1002/mma.860
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✦ Synopsis
Abstract
The least‐squares polynomial smoothing problem of discrete‐time signals from uncertain observations is addressed, when the variables describing the uncertainty are correlated at consecutive sampling times. Defining suitable augmented signal and observation vectors, the polynomial estimation problem is reduced to the linear estimation problem of the augmented signal. By an innovation
approach, recursive algorithms are derived for the augmented linear estimators without requiring the knowledge of the state‐space model generating the signal, but only covariance information of the processes involved. Copyright © 2007 John Wiley & Sons, Ltd.