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Conference papers
NEW FAST ALGORITHM FOR SIMULTANEOUS IDENTIFICATION AND OPTIMAL RECONSTRUCTION OF NON STATIONARY AR PROCESSES WITH MISSING OBSERVATIONS
Abstract : This paper deals with the problem of adaptive reconstruction and identification of AR processes with randomlymissing observations. A new real time algorithm is proposed. It uses combined pseudo-linear RLS algorithm and Kalman filter. It offers an unbiased estimation of the AR parameters and an optimal reconstruction error in the least mean square sense. In addition, thanks to the pseudo-linear RLS identification, this algorithm can be used for the identification of non stationary AR signals. Moreover, simplifications of the algorithm reduces the calculation time, thus this algorithm can be used in real time applications.
Cited literature [13 references]
https://hal-supelec.archives-ouvertes.fr/hal-00258330
Contributor : Karine El Rassi <>
Submitted on : Thursday, February 21, 2008 - 4:07:41 PM
Last modification on : Tuesday, June 30, 2020 - 4:04:07 PM
Document(s) archivé(s) le : Thursday, May 20, 2010 - 11:18:10 PM
Contributor : Karine El Rassi <>
Submitted on : Thursday, February 21, 2008 - 4:07:41 PM
Last modification on : Tuesday, June 30, 2020 - 4:04:07 PM
Document(s) archivé(s) le : Thursday, May 20, 2010 - 11:18:10 PM
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