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.
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Rawad Zgheib, Gilles Fleury, Elisabeth Lahalle. NEW FAST ALGORITHM FOR SIMULTANEOUS IDENTIFICATION AND OPTIMAL RECONSTRUCTION OF NON STATIONARY AR PROCESSES WITH MISSING OBSERVATIONS. Digital Signal Processing Workshop, Sep 2006, Grand Teton National Park, United States. pp. 371-376, ⟨10.1109/DSPWS.2006.265414⟩. ⟨hal-00258330⟩

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