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Generalized sentinels defined via least squares

Chavent, Guy (1995), Generalized sentinels defined via least squares, Applied Mathematics and Optimization, 31, 2, p. 189-218. http://dx.doi.org/10.1007/BF01182788

Type
Article accepté pour publication ou publié
External document link
https://hal.inria.fr/inria-00074742
Date
1995
Journal name
Applied Mathematics and Optimization
Volume
31
Number
2
Publisher
Springer
Pages
189-218
Publication identifier
http://dx.doi.org/10.1007/BF01182788
Metadata
Show full item record
Author(s)
Chavent, Guy
Abstract (EN)
We address the problem of monitoring a linear functional (c, x)Eof an unknown vectorx of a Hilbert spaceE, the available data being the observationz, in a Hilbert spaceF, of a vectorAx depending linearly onx through some known operatorAεℒ(E; F). WhenE=E 1×E 2,c=(c 1 0), andA is injective and defined through the solution of a partial differential equation, Lions ([6]–[8]) introduced sentinelssεF such that (s, Ax)Fis sensitive to x1 εE 1 but insensitive to x2 ε E2. In this paper we prove the existence, in the general case, of (i) a generalized sentinel (s, σ) ε ℱ ×E, where ℱ ⊃F withF dense in 80, such that for anya priori guess x0 ofx, we have 〈s, Ax〉ℱℱ + (σ, x0)E=(c, x)E, where x is the least-squares estimate ofx closest tox 0, and (ii) a family of regularized sentinels (s n , σ n ) ε F×E which converge to (s, σ). Generalized sentinels unify the least-squares approach (by construction !) and the sentinel approach (whenA is injective), and provide a general framework for the construction of “sentinels with special sensitivity” in the sense of Lions [8]).
Subjects / Keywords
Least squares; Sentinels; Optimal control; Regularization; Duality

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