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Title: Kolmogorov complexity, pseudorandom generators and statistical models testing (English)
Author: Šindelář, Jan
Author: Boček, Pavel
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 38
Issue: 6
Year: 2002
Pages: [747]-759
Summary lang: English
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Category: math
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Summary: An attempt to formalize heuristic concepts like strings (sequences resp.) “typical” for a probability measure is stated in the paper. Both generating and testing of such strings is considered. Kolmogorov complexity theory is used as a tool. Classes of strings “typical” for a given probability measure are introduced. It is shown that no pseudorandom generator can produce long strings from the classes. The time complexity of pseudorandom generators with oracles capable to recognize “typical” strings is shown to be at least exponential with respect to the length of the output. Tests proclaiming some strings “typical” are introduced. We show that the problem of testing strings to be “typical” is undecidable. As a consequence, the problem of correspondence between probability measures and data is undecidable too. If the Lebesgue measure is considered, then the conditional probability of failure of a test is shown to exceed a positive lower bound almost surely. (English)
Keyword: Kolmogorov complexity
Keyword: typical string
Keyword: pseudorandom generator
MSC: 60A10
MSC: 65C10
MSC: 68Q30
idZBL: Zbl 1265.68083
idMR: MR1954395
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Date available: 2009-09-24T19:50:22Z
Last updated: 2015-03-26
Stable URL: http://hdl.handle.net/10338.dmlcz/135500
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Reference: [9] Šindelář J., Boček P.: Kolmogorov complexity and probability measures.Kybernetika 38 (2002), 729–745 MR 1954394
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