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Recursive parameter estimation for noisy autoregressive signals (Corresp.)

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1 Author(s)

The problem of recursively estimating the unknown parameters of a scalar autoregressive (AR) signal observed in additive white noise, including signal power and noise variance, is considered. A state-space model in a canonical but noninnovations form is used to represent the noisy AR signal. An algorithm based on a system identification/parameter estimation technique known as the recursive prediction error method is presented for recursive parameter estimation. Two simulation examples illustrate the effectiveness of the proposed algorithm.

Published in:

IEEE Transactions on Information Theory  (Volume:32 ,  Issue: 3 )