On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms

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 allow to obtain tracking error bound but 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. keywords 60G35, 93E10, 93E12, 93E15, 93E23 Corresponding author: E. Moulines, Ecole Nationale Superieure des Telecommunications, CNRS-URA 820, 46, rue Barrault, 75634 Paris Cedex 13, FRANCE R. Aguech, Laboratoire de Probabilites, Universite Pierre et Marie Curie, 4 Place Jussieu, 75252 Paris FRANCE P. Priouret, Laboratoire de Probabilites, Universite Pierre et Marie Curie, 4 Place Jussieu, 75252 Paris FRANCE 1 

• Type: Journal
• Year: 2000
• Where: SIAMCO
• Authors: Rafik Aguech, Eric Moulines, Pierre Priouret
• Keywords: Pierre Et Marie, SIAMCO 2000, Tracking Error, Universite Pierre Et Marie Curie