Adaptive algorithm for noisy autoregressive signals

Wei Xing Zheng

doi:10.1155/S1024123X00001472

Adaptive algorithm for noisy autoregressive signals

Research output: Contribution to journal › Article

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.

Original language	English
Pages (from-to)	543-556
Number of pages	14
Journal	Mathematical Problems in Engineering
Volume	6
Issue number	6
DOIs	https://doi.org/10.1155/S1024123X00001472
Publication status	Published - 2001

Keywords

adaptive algorithms
adaptive filters
autoregressive signals
parameter estimation
Parameter estimation
Adaptive algorithms
Adaptive filtering
Autoregressive signals
Noisy signals

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10.1155/S1024123X00001472

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title = "Adaptive algorithm for noisy autoregressive signals",

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.",

keywords = "adaptive algorithms, adaptive filters, autoregressive signals, parameter estimation, Parameter estimation, Adaptive algorithms, Adaptive filtering, Autoregressive signals, Noisy signals",

author = "Zheng, {Wei Xing}",

year = "2001",

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language = "English",

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AB - 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.

KW - adaptive algorithms

KW - adaptive filters

KW - autoregressive signals

KW - parameter estimation

KW - Parameter estimation

KW - Adaptive algorithms

KW - Adaptive filtering

KW - Autoregressive signals

KW - Noisy signals

UR - http://handle.uws.edu.au:8081/1959.7/33933

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DO - 10.1155/S1024123X00001472

M3 - Article

SN - 1024-123X

VL - 6

SP - 543

EP - 556

JO - Mathematical Problems in Engineering

JF - Mathematical Problems in Engineering

IS - 6

ER -

Adaptive algorithm for noisy autoregressive signals

Abstract

Keywords

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