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On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms
Journal article   Peer reviewed

On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms

Rafik Aguech, Eric Moulines and Pierre Priouret
SIAM journal on control and optimization, Vol.39(3), pp.872-899
2000
DOI: https://doi.org/10.1137/S0363012998333852

Abstract

Algorithms Approximation Decomposition Noise Signal processing
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 results in a tracking error bound and tight approximate expressions for the moments of the tracking error. These expressions allow the evaluation, both qualitatively and quantitatively, of the impact of several factors on the tracking error performance.

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