Presentation	2000/3/17 Embedding Theorem for Multivariable Input Systems and Causality Analyses Tohru Ikeguchi,
PDF Download Page	PDF download Page Link
Abstract(in Japanese)	(See Japanese page)
Abstract(in English)	We propose a method for analyzing causal relations between time series sets from the view point of nonlinear dynamical systems. Mathematical background for the present issue is an extension of embedding theories of autonomous systems to forced systems, or input-output systems. We extend the conventional embedding theorem to a new version, which can be applied to not only systems with a single input but also those with multivariable inputs. We discuss possible detection of nonlinear causal relation by nonlinear predictability of output sequences with information of input sequences. We show several examples for confirming the proposed framework.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	Nonlinear / Chaos / Embedding theorem / Causality / Surrogate data
Paper #	NLP99-154
Date of Issue

Conference Information
Committee	NLP
Conference Date	2000/3/17(1days)
Place (in Japanese)	(See Japanese page)
Place (in English)
Topics (in Japanese)	(See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To	Nonlinear Problems (NLP)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Embedding Theorem for Multivariable Input Systems and Causality Analyses
Sub Title (in English)
Keyword(1)	Nonlinear
Keyword(2)	Chaos
Keyword(3)	Embedding theorem
Keyword(4)	Causality
Keyword(5)	Surrogate data
1st Author's Name	Tohru Ikeguchi
1st Author's Affiliation	Department of Applied Electronics, Science University of Tokyo()
Date	2000/3/17
Paper #	NLP99-154
Volume (vol)	vol.99
Number (no)	714
Page	pp.pp.-
#Pages	8
Date of Issue