Title :
On a perturbation approach for the analysis of stochastic tracking algorithms
Author :
Moulines, E. ; Priouret, P. ; Aguech, R.
Author_Institution :
ENST, Paris, France
Abstract :
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
Keywords :
adaptive systems; error analysis; perturbation techniques; statistical analysis; stochastic systems; tracking; decomposition; general adaptive tracking algorithm; linear regression model; moments; perturbation approach; perturbation expansion technique; stochastic tracking algorithms; tight approximate expressions; tracking error; tracking error bound; Algorithm design and analysis; Difference equations; Linear regression; Noise measurement; Random processes; Signal processing; Signal processing algorithms; Stochastic processes; Stochastic resonance; System identification;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.681779
