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Parameter estimation with expected and residual-at-risk criteria
2008
2008 47th IEEE Conference on Decision and Control
In this paper we study a class of uncertain linear estimation problems in which the data are affected by random uncertainty. In this setting, we consider two estimation criteria, one based on minimization of the expected 1 or 2 norm residual and one based on minimization of the level within which the 1 or 2 norm residual is guaranteed to lie with an a-priori fixed probability (residual at risk). The random uncertainty affecting the data is characterized by means of its first two statistical
doi:10.1109/cdc.2008.4738597
dblp:conf/cdc/CalafioreTG08
fatcat:q25we6rji5aolozvd4qkujtnre