Unfalsified weighted least squares estimates in set-membership identification

Er-Wei Bai; Li Qiu; Roberto Tempo

doi:10.1109/81.660752

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Journal article

Unfalsified weighted least squares estimates in set-membership identification

Er-Wei Bai, Li Qiu and Roberto Tempo

IEEE transactions on circuits and systems. 1, Fundamental theory and applications, Vol.45(1), pp.41-49

1998

DOI: 10.1109/81.660752

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Abstract

It is well known that the weighted least squares (WLS) identification algorithm provides estimates that are in general not in the membership set and in this sense are falsified estimates. This paper shows that: (1) if the noise bound is known, the WLS estimates can be made to lie in or converge to the membership set by choosing the weights properly and (2) if the noise bound is unknown, the same results can still be achieved by using white input signals for finite impulse response systems (FIR).

Applied Sciences

Signal and communications theory

Telecommunications and information theory

Exact sciences and technology

Signal, noise

Information, signal and communications theory

Detection, estimation, filtering, equalization, prediction

Details

Title: Subtitle: Unfalsified weighted least squares estimates in set-membership identification
Creators: Er-Wei Bai - University of Iowa, Iowa City, IA 52242, United States
Li Qiu - Department of Electrical Engineering, Hong Kong Univeristy of Science and Technology, Clear Water Bay, Kowloon, Hong-Kong
Roberto Tempo - National Research Council of Italy, Politecnico di Torino, Torino, Italy
Resource Type: Journal article
Publication Details: IEEE transactions on circuits and systems. 1, Fundamental theory and applications, Vol.45(1), pp.41-49
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/81.660752
ISSN: 1057-7122
eISSN: 1558-1268
Language: English
Date published: 1998
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984083819202771

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