@inproceedings{5446eb823e254f3ea1248d04a3cfe46f,
title = "Information inequality for estimation of transfer functions: Main results",
abstract = "In this paper we derive a canonical lower bound for the autocovariance function of any unbiased transfer-function estimator. As a generalization of the Cram{\'e}r-Rao bound, the Cram{\'e}r-Rao kernel that we define can be derived without parametrizing the model set. The Cram{\'e}r-Rao kernel is thus one of the cornerstones for experiment design formulations that do not depend on the choice of coordinates.",
keywords = "Autocovariance, Confidence region, Fisher information, Information geometry, Metric, Reproducing kernel, System identification",
author = "Tzvetan Ivanov and Anderson, {Brian D.O.} and Absil, {P. A.} and Michel Gevers",
year = "2011",
doi = "10.3182/20110828-6-IT-1002.00806",
language = "English",
isbn = "9783902661937",
series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",
publisher = "IFAC Secretariat",
number = "1 PART 1",
pages = "9959--9965",
booktitle = "Proceedings of the 18th IFAC World Congress",
edition = "1 PART 1",
}