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Unbiased parameter estimation of nonstationary signals in noise

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3 Author(s)
Alengrin, G. ; Université de Nice, Nice Cedex, France ; Barlaud, M. ; Menez, J.

Recent approaches to the modeling of nonstationary signals by means of AR or ARMA models use a representation with time-varying parameters. The time-varying parameters are assumed to be linear combinations of a set of basis time functions so that the model is specified by constant parameters. For stationary signals disturbed by white noise, an approach based upon a modified least-squares method leads to a good unbiased estimator of the parameters. In this correspondence, a similar algorithm deriving the unbiased parameters for nonstationary signals in white noise is given. The experimental results show the good performance of the proposed estimator.

Published in:

Acoustics, Speech and Signal Processing, IEEE Transactions on  (Volume:34 ,  Issue: 5 )

Date of Publication:

Oct 1986

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