Presentation | 1996/6/21 Inferring Invariant Measures of Dynamical Systems Ken UMENO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We consider the problem of inferring invariant measures of dynamical systems. To solve the problem, we give a new class of ergordic mappings whose invariant measure is absolutely continuous with respect to the Lebesgue measure using the addition formula of hyper-elliptic functions. In this class of ergordic dynamical systems, this inverse problem is shown to be transformed to be the statistical inference problem in the standard sense. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Chaos / invariant measures / Neumann=Ulam map / statistical inference |
Paper # | NC96-13 |
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Conference Information | |
Committee | NC |
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Conference Date | 1996/6/21(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Inferring Invariant Measures of Dynamical Systems |
Sub Title (in English) | |
Keyword(1) | Chaos |
Keyword(2) | invariant measures |
Keyword(3) | Neumann=Ulam map |
Keyword(4) | statistical inference |
1st Author's Name | Ken UMENO |
1st Author's Affiliation | Laboratory for Information Representation, FRP, The Institute of Physical and Chemical Research (RIKEN)() |
Date | 1996/6/21 |
Paper # | NC96-13 |
Volume (vol) | vol.96 |
Number (no) | 117 |
Page | pp.pp.- |
#Pages | 6 |
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