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A modified identification algorithm for linear systems with noisy input-output data

Research output: Chapter in Book / Conference PaperConference Paper

Abstract

In this paper a modified identification algorithm for linear systems with noisy input-output data is developed. The main idea is to introduce extra equations so that the variances of the input noise and the output noise, which determine the noise-induced bias in the least-squares parameter estimator, can be estimated in a more accurate and quicker way. Due to this, such performance as estimation accuracy and convergence speed of the bias-correction based algorithm can be significantly boosted, at the expense of a fractional increase in the numerical cost. Computer simulations are presented, which leads to some useful conclusions.
Original languageEnglish
Title of host publicationProceedings of the 2002 IEEE International Symposium on Circuits and Systems held on May 26-29, 2002 at Fairmont Scottsdale Princess, Phoenix-Scottsdale, Arizona, USA
PublisherIEEE Press
Number of pages1
ISBN (Print)0780374487
Publication statusPublished - 2002
EventIEEE International Symposium on Circuits and Systems -
Duration: 20 May 2012 → …

Conference

ConferenceIEEE International Symposium on Circuits and Systems
Period20/05/12 → …

Keywords

  • signal processing
  • electric filters
  • electronics
  • linear systems
  • least squares
  • parameter estimation

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