Please use this identifier to cite or link to this item:
http://hdl.handle.net/10662/17945
Title: | Filtering and fixed-point smoothing from an innovation approach in systems with uncertainty |
Authors: | Caballero Águila, Raquel Hermoso Carazo, Aurora Linares Pérez, Josefa Jiménez López, José Domingo |
Keywords: | Innovación en sistemas de incertidumbre;Sistemas con observación incierta;Innovation in systems with uncertainty;Systems with uncertain observations |
Issue Date: | 2003 |
Publisher: | Universidad de Extremadura, Servicio de Publicaciones |
Abstract: | In this paper the least mean-squared error linear filtering and fixed- point smoothing problems in systems with uncertain observations are treated, assuming that the state-space model is not available. It is supposed that the variables describing the uncertainty are independent and the covariance matrix of the signal is known and presents a factorization in a semidegenerate kernel form. By applying an innovation approach, recursive algorithms for the filtering and fixed-point smoothing estimates are obtained; also, formulas for the error covariance matrices of the proposed estimators are presented. |
URI: | http://hdl.handle.net/10662/17945 |
ISSN: | 0213-8743 |
Appears in Collections: | Extracta Mathematicae Vol. 18, nº 1 (2003) |
Files in This Item:
File | Description | Size | Format | |
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2605-5686_18_1_119.pdf | 129,5 kB | Adobe PDF | View/Open |
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