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On a perturbation approach for the analysis of stochastic tracking algorithms
Conference proceeding

On a perturbation approach for the analysis of stochastic tracking algorithms

E. Moulines, P. Priouret, R. Aguech and IEEE
Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), Vol.3, pp.1681-1684 vol.3
1998
DOI: https://doi.org/10.1109/ICASSP.1998.681779

Abstract

Algorithm design and analysis Difference equations Linear regression Noise measurement Random processes Signal processing Signal processing algorithms Stochastic processes Stochastic resonance System identification
In this paper, a perturbation expansion technique is introduced to decompose the tracking error of a general adaptive tracking algorithm in a linear regression model. This method allows to obtain the tracking error bound and also tight approximate expressions for the moments of the tracking error. These expressions allow to evaluate, both qualitatively and quantitatively, the impact of several factors on the tracking error performance which have been overlooked in previous contributions.

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