Adaptive parameter estimation of autoregressive signals from noisy observations

被引：0
|
作者：
Zheng, WX [1 ]
机构：
[1] Univ Western Sydney Nepean, Sch Sci, Sydney, NSW 2747, Australia
来源：
ICSP '98: 1998 FOURTH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, PROCEEDINGS, VOLS I AND II | 1998年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：449 / 452
页数：4
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