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An individual ergodic theorem for fuzzy random variables. (English) Zbl 0551.60036

In probability theory, the strong law of large numbers is just a special case of ergodic theorem. The present authors have proved a strong law of large numbers for Kwakernaak’s fuzzy random variables (see the foregoing review, Zbl 0551.60035). This work generalizes it to an individual ergodic theorem. If T is a measure-preserving transformation on a probability space (\(\Omega\),\({\mathcal A},P)\), then,
(1) for any frv \(\xi\) on (\(\Omega\),\({\mathcal A},P)\), \(n^{-1}\sum^{n- 1}_{k=0}\xi (T^ k\omega)\) converges a.s.,
(2) the limit, denoted by \(\xi^*\), is a frv and invariant, i.e., \(\xi^*(T^ n\omega)=\xi^*(\omega)\) a.s. \((n=0,\pm 1,\pm 2,...),\)
(3) \(E\xi^*=E\xi,\)
(4) if T is an ergodic measure-preserving transformation, \(\xi^*(\omega)=E\xi\) a.s.
This is a generalization of Birkhoff’s individual ergodic theorem to the fuzzy situation.
Reviewer: Y.Qu

MSC:

60F15 Strong limit theorems
94D05 Fuzzy sets and logic (in connection with information, communication, or circuits theory)
60A99 Foundations of probability theory

Citations:

Zbl 0551.60035
Full Text: DOI

References:

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