Extended Admissible Control for the Linear-Gaussian State-Observation Model
definitionProbabilitydef:extended-admissible-control-2026aConsider a \reftext{def:linear-gaussian-state-observation-model-2026a}{linear-Gaussian state-observation model} on , with notation and fixed versions as there, and let be a \reftext{def:natural-numbers-2026a}{natural number}. Adopt the notation , of \reftext{lem:interval-lebesgue-toolkit-2026a}{the restricted Lebesgue measure on }, and the distance between \reftext{def:admissible-control-2026a}{admissible controls} of \ref{lem:control-sequence-mean-square-limit-2026a}.
An \textbf{extended admissible control with values in } for the model is a \reftext{def:family-subfamily-subsets-set-2026a}{family} , where each is a tuple of \reftext{def:square-integrable-mean-square-2026a}{square-integrable} random variables on , such that:
\textbf{(i)} for every and every , the random variable is \reftext{def:almost-surely-2026a}{almost surely} equal to a -measurable square-integrable random variable, where is the observation -algebra of the model itself, without control, and measurability means that preimages of \reftext{def:borel-sigma-algebra-real-line-2026a}{Borel sets} belong to ;
\textbf{(ii)} there exist a \reftext{def:sequence-in-set-2026a}{sequence} of admissible controls with values in and a set with such that the sequence is Cauchy for in the sense of \ref{lem:control-sequence-mean-square-limit-2026a}, and for every and every the real sequence has \reftext{def:limit-sequence-real-c54-2026a}{limit} , with the mean-square norm of \ref{def:square-integrable-mean-square-2026a}.
A pair as in (ii) is called an \textbf{approximating sequence} for .
Prerequisites
No prerequisites tracked.
Dependents
No dependents yet.
Dependent proofs
No dependent proofs yet.
Authors
Loading…