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Analysis of linear methods for robust identification in ℓ1

✍ Scribed by J.R. Partington; P.M. Mäkilä

Publisher
Elsevier Science
Year
1995
Tongue
English
Weight
485 KB
Volume
31
Category
Article
ISSN
0005-1098

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✦ Synopsis

We consider worst-case analysis of system identification by means of the linear algorithms such as least-squares. We provide estimates for worst-case and average errors, showing that worst-case robust convergence cannot occur in the .5', identification problem. The case of periodic inputs is also analysed. Finally a pseudorandomness assumption is introduced that allows more powerful convergence results in a deterministic framework.

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