- Title
- A stochastic approach to estimation in H∞
- Creator
- Ninness, Brett
- Relation
- Automatica Vol. 34, Issue 1, p. 405-414
- Publisher Link
- http://dx.doi.org/10.1016/S0005-1098(97)00219-7
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 1998
- Description
- This paper examines the problem of system identification from frequency response data. Recent approaches to this problem, known collectively as "Estimation in H∞", involve deterministic descriptions of noise corruptions to the data. In order to provide "worst-case" convergence with respect to these deterministic noise descriptions, non-linear in the data algorithms are required. In contrast, this paper examines "worst-case" estimation in H infinity when the disturbances are subject to mild stochastic assumptions and linear in the data algorithms are employed. Issues of convergence, error bounds, and model order selection are considered.
- Subject
- estimation theory; algorithms; system identification; robust estimation; error analysis
- Identifier
- uon:2743
- Identifier
- http://hdl.handle.net/1959.13/31204
- Identifier
- ISSN:0005-1098
- Language
- eng
- Full Text
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