Decomposition based fast least squares algorithm for output error systems

Parameter estimation methods have wide applications in signal processing, communication and system identification. This paper derives an iterative least squares algorithm to estimate the parameters of output error systems and uses the partitioned matrix inversion lemma to implement the proposed algo...

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Bibliographic Details
Published in:Signal processing Vol. 93; no. 5; pp. 1235 - 1242
Main Author: Ding, Feng
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.05.2013
Elsevier
Subjects:
Algorithms
Applied sciences
Communication systems
Computational efficiency
Computer simulation
Detection, estimation, filtering, equalization, prediction
Errors
Exact sciences and technology
Fast least squares
Filtering
Information, signal and communications theory
Inversions
Iterative algorithm
Least squares method
Parameter estimation
Signal and communications theory
Signal processing
Signal, noise
Telecommunications and information theory
Signal processing
Iterative algorithm
Parameter estimation
Filtering
Fast least squares
Performance evaluation
Iterative method
Implementation
Simulation
Matrix inversion
Least squares method
Telecommunication system
System identification
Fast algorithm
ISSN:0165-1684, 1872-7557
Online Access:Get full text
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Summary:Parameter estimation methods have wide applications in signal processing, communication and system identification. This paper derives an iterative least squares algorithm to estimate the parameters of output error systems and uses the partitioned matrix inversion lemma to implement the proposed algorithm in order to enhance computational efficiencies. The simulation results show that the proposed algorithm works well. ► An iterative least squares algorithm is presented for output error systems. ► The proposed algorithm is implemented by using the partitioned matrix inversion. ► The proposed algorithm has high computational efficiencies.
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ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2012.12.013