Bounded error parameter estimation: a sequential analytic center approach

Er-Wei Bai; Yinyu Ye; Roberto Tempo

doi:10.1109/9.769366

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Bounded error parameter estimation: a sequential analytic center approach

Journal article

Peer reviewed

Bounded error parameter estimation: a sequential analytic center approach

Er-Wei Bai, Yinyu Ye and Roberto Tempo

IEEE transactions on automatic control, Vol.44(6), pp.1107-1117

06/1999

DOI: 10.1109/9.769366

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Abstract

A sequential analytic center approach for bounded error parameter estimation is proposed. The authors show that the analytic center minimizes the logarithmic average output error among all the estimates within the membership set and is a maximum likelihood estimator for a class of noise density functions which include parabolic densities and approximations of truncated Gaussian. They also show that the analytic center is easily computable for both offline and online problems with a sequential algorithm. The convergence proof of this sequential algorithm is obtained and, moreover, it is shown that the complexity in terms of the maximum number of Newton iterations is linear in the number of observed data points.

Algorithm design and analysis

Maximum likelihood estimation

Parameter estimation

Error analysis

Acoustic noise

Stochastic resonance

Gaussian noise

Cities and towns

Density functional theory

System identification

Details

Title: Subtitle: Bounded error parameter estimation: a sequential analytic center approach
Creators: Er-Wei Bai - Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA
Yinyu Ye
Roberto Tempo
Resource Type: Journal article
Publication Details: IEEE transactions on automatic control, Vol.44(6), pp.1107-1117
Publisher: IEEE
DOI: 10.1109/9.769366
ISSN: 0018-9286
eISSN: 1558-2523
Language: English
Date published: 06/1999
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984083819402771

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