Mathematical Problems in Engineering
Volume 6 (2001), Issue 6, Pages 543-556
doi:10.1155/S1024123X00001472
Adaptive algorithm for noisy autoregressive signals
School of Science, University of Western Sydney, Nepean, Kingswood, Sydeny NSW 2747, Australia
Received 15 February 2000
Copyright © 2001 Wei Xing Zheng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper presents a new type of improved least-squares (ILS) algorithm for adaptive parameter estimation of autoregressive (AR) signals from noisy observations. Unlike the previous ILS based methods, the developed algorithm can give consistent parameter estimates in a very direct manner that it does not involve dealing with an augmented noisy AR model. The new algorithm is demonstrated to outperform the previous ILS based methods in terms of its improved numerical efficiency.