DocumentCode
2861384
Title
Adaptive parameter estimation of autoregressive signals from noisy observations
Author
Zheng, Wei Xing
Author_Institution
Sch. of Sci., Western Sydney Univ., Kingswood, NSW, Australia
fYear
1998
fDate
1998
Firstpage
449
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 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
Keywords
adaptive signal processing; autoregressive processes; least squares approximations; parameter estimation; AR signals; ILS algorithm; adaptive parameter estimation; autoregressive signals; improved least-squares algorithm; noisy observations; numerical efficiency; performance; Adaptive estimation; Australia; Equations; Multilevel systems; Noise cancellation; Parameter estimation; Signal processing algorithms; Speech analysis; White noise; Yield estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-4325-5
Type
conf
DOI
10.1109/ICOSP.1998.770247
Filename
770247
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