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This article is cited in 33 scientific papers (total in 33 papers)
Effective convergence in probability and an ergodic theorem for individual random sequences
V. V. V'yugin Institute for Information Transmission Problems, Russian Academy of Sciences
Abstract:
An algorithmic analysis of the ergodic theorem for a measure-preserving transformation is given. We prove that the classical ergodic theorem is not algorithmically effective. We present a formulation and a proof of the ergodic theorem for individual random sequences based on A. N. Kolmogorov's algorithmic approach to the substantiation of the theory of probability and information theory.
Keywords:
ergodic theorem, quasiergodic theorem, stationary measure, convergence in probability, convergence almost everywhere, algorithm, random sequence, algorithmical randomness.
Received: 12.07.1996
Citation:
V. V. V'yugin, “Effective convergence in probability and an ergodic theorem for individual random sequences”, Teor. Veroyatnost. i Primenen., 42:1 (1997), 35–50; Theory Probab. Appl., 42:1 (1998), 39–50
Linking options:
https://www.mathnet.ru/eng/tvp1710https://doi.org/10.4213/tvp1710 https://www.mathnet.ru/eng/tvp/v42/i1/p35
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Abstract page: | 437 | Full-text PDF : | 246 | First page: | 19 |
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