Presentation	2005/11/11 Stochastic processes generating power law fluctuations and information theory AKIHIRO Sato,
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Abstract(in English)	The Langevin equations with both multiplicative and additive noises, of which steady-state probability density functions have power law tails are theoretically investigated. Information theory is applied to their steady-state probability density functions and their Fisher information is derived in the case of a static input signal. Moreover it is shown that the static input signal can be estimated from a difference between function forms of the observed probability density functions.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	power law tails / stationary probability density functions / Kullbakc-Leibler information / Fisher information
Paper #	NLP2005-65,NC2005-57
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Conference Information
Committee	NC
Conference Date	2005/11/11(1days)
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Paper Information
Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Stochastic processes generating power law fluctuations and information theory
Sub Title (in English)
Keyword(1)	power law tails
Keyword(2)	stationary probability density functions
Keyword(3)	Kullbakc-Leibler information
Keyword(4)	Fisher information
1st Author's Name	AKIHIRO Sato
1st Author's Affiliation	Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University()
Date	2005/11/11
Paper #	NLP2005-65,NC2005-57
Volume (vol)	vol.105
Number (no)	418
Page	pp.pp.-
#Pages	5
Date of Issue