NDLI: Bias compensation-based recursive least-squares estimation with forgetting factors for output error moving average systems

Content Provider	IET Digital Library
Author	Wu, Ai Guo Qian, Yang Yang Wu, Wei Jun
Abstract	The bias compensation technique combined with the least-squares estimation algorithm with forgetting factors is applied to the parameter estimation of output error models with moving average noise. It is shown that the bias term induced by the noise is determined by the weighted average variance of the white noise and the parameters of the unknown noise model. Therefore, in order to give a recursive estimation of the bias term, an interactive estimation of the weighted average variance and noise parameters is constructed by using the principle of hierarchical identification. In addition, a recursive form is also established to estimate the so-called weighted average variance of the white noise. The estimation algorithm is finally established by combining the interactive estimation and the recursive estimation of weighted average variance. A simulation example is employed to show the effectiveness of the proposed bias compensation based least-squares estimation algorithm with two forgetting factors.
Starting Page	483
Ending Page	494
Page Count	12
ISSN	17519675
Volume Number	8
e-ISSN	17519683
Issue Number	Issue 5, Jul (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/8/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2013.0327
Journal	IET Signal Processing
Publisher Date	2013-11-28
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Autoregressive Moving Average Processes Bias Compensation-based Recursive Least-squares Estimation Algorithm Compensation Hierarchical Identification Interactive Estimation Interpolation And Function Approximation Least Squares Approximation Numerical Analysis Output Error Model Output Error Moving Average System Parameter Estimation Recursive Estimation Signal Processing Signal Processing And Detection Signal Processing Theory Statistics Weighted Average Variance White Noise
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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