A robust, parallelizable, \(O(m)\), a posteriori recursive least squares algorithm for efficient adaptive filtering
type: Item
instance of: scholarly article
zbMATH Open document ID: 1009.93077
DOI: 10.1109/78.782203
author: Constantin Papaodysseus
published in: IEEE Transactions on Signal Processing
publication date: 2002-03-19T00:00:00Z
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 93E24
Mathematics Subject Classification ID: 65Y05
zbMATH DE Number: 1632248
zbMATH Keywords: adaptive filtering
zbMATH Keywords: RLS algorithms
zbMATH Keywords: finite memory filtering
zbMATH Keywords: tracking
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1109/78.782203
OpenAlex ID: W2120082487
title: A robust, parallelizable, \(O(m)\), a posteriori recursive least squares algorithm for efficient adaptive filtering
review text: The paper presents a new recursive least squares finite memory adaptive filtering algorithm. Its main properties are small tracking error, high speed of convergence and simple stabilizability. Furthermore, it can be easily parallelized, thus resulting in a particularly fast algorithm, and its stabilized version appears to be suitable also for nonstationary signals. The results of a few applications to real data are shown.
reviewed by: Giovanni Di Masi
description: scientific article; zbMATH DE number 1632248