Tracking Dynamic Systems in α-Stable Environments

Sayed Pouria Talebi; Stefan Werner; Shengxi Li; Danilo P. Mandic

ICASSP 2019accepted0 citations

Tracking Dynamic Systems in α-Stable Environments

Sayed Pouria Talebi, Stefan Werner, Shengxi Li, Danilo P. Mandic

Abstract

In order to accommodate for modern adaptive filtering applications, the classic adaptive filtering paradigm is considered from a more general perspective. The new formulation allows for time dependent variations in the state of the system and more importantly it relaxes the Gaussian assumption to the generalized setting of α-stable distributions. In this work, based on the principles of gradient descent and fractional-order calculus, a cost-effective technique for tracking the state of such a system is derived. For rigour, performance of the derived filtering technique is analyzed and convergence conditions are established.

BibTeX

@inproceedings{icassp2019_trackingdynamics,
  title = {Tracking Dynamic Systems in α-Stable Environments},
  author = {Sayed Pouria Talebi and Stefan Werner and Shengxi Li and Danilo P. Mandic},
  booktitle = {ICASSP 2019},
  year = {2019}
}