Stochastic embedding revisited: a modern interpretation

Title: Stochastic embedding revisited: a modern interpretation
Creator: Ljung, Lennart; Goodwin, Graham C.; Aguero, Juan C.
Relation: 53rd Institute of Electrical and Electronics Engineers (IEEE) Conference on Decision and Control. Proceedings of the 53rd Institute of Electrical and Electronics Engineers (IEEE) Conference on Decision and Control (Los Angeles, CA 15-17 December, 2014) p. 3340-3345
Publisher Link: http://dx.doi.org/10.1109/CDC.2014.7039906
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Resource Type: conference paper
Date: 2014
Description: There is a very extensive literature on various aspects of the central Bias-Variance trade-off in linear system identification. In the 80's and 90's the focus was on bias characterization, model error models and Stochastic Embedding. Recently, there has been a new interest in Bayesian or kernel methods. This paper puts part of this literature into perspective by giving a modern interpretation of the Stochastic Embedding approach.
Subject: stochastic processes; vectors; uncertainty; computational modeling; kernel; estimation; frequency-domain analysis
Identifier: http://hdl.handle.net/1959.13/1342619
Identifier: uon:28993
Identifier: ISSN:0191-2216
Language: eng
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