In the present paper, we study bundle convergence in JW- algebra and prove certain ergodic theorems with respect to such convergence. Moreover, conditional expectations of reversible JW-algebras are considered. Using such expectations, the convergence of supermartingales is established.
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We consider Markov chains represented in the form Xn+1 = f (Xn, In), where {In} is a sequence of independent, identically distributed (i.i.d.) random variables, and where f is a measurable function. Any Markov chain {Xn} on a Polish state space may be represented in this form i.e. can be considered as arising from an iterated function system (IFS). A distributional ergodic theorem, including rates of convergence in the Kantorovich distance is proved for Markov chains under the condition that an IFS representation is "stochastically contractive" and "stochastically bounded". We apply this result to prove our main theorem giving upper bounds for distances between invariant probability measures for iterated function systems. We also give some examples indicating how ergodic theorems for Markov chains may be proved by finding contractive IFS representations. These ideas are applied to some Markov chains arising from iterated function systems with place dependent probabilities.
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In [2] Jajte formulated the following question: Let h0 (x) and h1 (x) be homeomorphisms of the interval [0, 1] onto itself. Is it true that for any x € [0, 1] and almost any t ϵ (0, 1) there exists a limit of a sequence [formula] for n → ∞, where t = (0, t1 t2…)2 is a binary representation of t, i.e. t = Σi ≥ 1 ti 2-i and ti ϵ {0, 1}? The answer is negative. We describe the set of condensation points of the sequence in some special cases.
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