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- W4293662854 abstract "The construction presented in this paper can be briefly described as follows: starting from any finite-dimensional Markov transition function p_t, on a measurable state space (E,B), we construct a strong Markov process on a certain intrinsic state space that is, in fact, a closed subset of a finite dimensional Euclidean space R^d. Of course we must explain the meaning of finite-dimensionality and intrinsity. Starting with p_t, we consider the range of the nonnegative bounded measurable functions under the action of the resolvent. This class of functions induces a uniform structure on E. We say that E is finite-dimensional if this uniformity is finitely generated. In such cases we then map E into R^d. The intrinsic state space is the closure of the range of this mapping. On this enlarged state space we construct a strong Markov process, which corresponds quite naturally to p_t. We give several examples including the usual examples of nonstrong Markov process." @default.
- W4293662854 created "2022-08-31" @default.
- W4293662854 creator A5083969173 @default.
- W4293662854 date "2013-03-11" @default.
- W4293662854 modified "2023-09-23" @default.
- W4293662854 title "Constructing Strong Markov Processes" @default.
- W4293662854 doi "https://doi.org/10.48550/arxiv.1303.2670" @default.
- W4293662854 hasPublicationYear "2013" @default.
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