Presentation	2009-08-04 A detection method to a dynamical system change in time series prediction using an ART Daisuke HANASHIRO, Hidehiro NAKANO, Arata MIYAUCHI,
PDF Download Page	PDF download Page Link
Abstract(in Japanese)	(See Japanese page)
Abstract(in English)	Time series prediction is based on estimating a system which generates time series and constructing a system model which approximates the system. However, if the system is changed by external factors, it is needed to detect the change correctly and to reconstruct the system model. In this paper, we propose a detection method to a dynamic system change using an ART. For noisy time series, the proposed method can detect the dynamic system change with high accuracy. Through numerical experiments, effectiveness of the proposed method is confirmed.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	Time Series Prediction / Adaptive Resonance Theory / Time-Variant System
Paper #	NLP2009-54
Date of Issue

Conference Information
Committee	NLP
Conference Date	2009/7/27(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)	A detection method to a dynamical system change in time series prediction using an ART
Sub Title (in English)
Keyword(1)	Time Series Prediction
Keyword(2)	Adaptive Resonance Theory
Keyword(3)	Time-Variant System
1st Author's Name	Daisuke HANASHIRO
1st Author's Affiliation	Tokyo City University()
2nd Author's Name	Hidehiro NAKANO
2nd Author's Affiliation	Tokyo City University
3rd Author's Name	Arata MIYAUCHI
3rd Author's Affiliation	Tokyo City University
Date	2009-08-04
Paper #	NLP2009-54
Volume (vol)	vol.109
Number (no)	167
Page	pp.pp.-
#Pages	5
Date of Issue