Unifying some higher-order statistic-based methods for errors-in-variables model identification Thil, Stephane; Zheng, Wei Xing; Gilson, Marion; ...

User activity

Share to:
View the summary of this work
Authors
Thil, Stephane ; Zheng, Wei Xing ; Gilson, Marion ; Garnier, Hugues
Subjects
automaton; instrumental variable; higher-order statistics
Summary
In this paper, the problem of identifying linear discrete-time systems from noisy input and output data is addressed. Several existing methods based on higher-order statistics are presented. It is shown that they stem from the same set of equations and can thus be united from the viewpoint of extended instrumental variable methods. A numerical example is presented which confirms the theoretical results. Some possible extensions of the methods are then given.
Bookmark
http://trove.nla.gov.au/work/194371
Work ID
194371

User activity


e.g. test cricket, Perth (WA), "Parkes, Henry"

Separate different tags with a comma. To include a comma in your tag, surround the tag with double quotes.

Be the first to add a tag for this work

Be the first to add this to a list

Comments and reviews

What are comments? Add a comment

No user comments or reviews for this work

Add a comment


Show comments and reviews from Amazon users