- 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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