Summary
International Symposium on Nonlinear Theory and Its Applications
2016
Session Number:A2L-B
Session:
Number:A2L-B-1
Detecting Bifurcations from Time Series Data
Kazuto Ogoshi, Hiroyuki Kitajima, Toru Yazawa,
pp.-
Publication Date:2016/11/27
Online ISSN:2188-5079
Summary:
In this paper, we try to detect the early-warning signal from time series data. A simple mathematical model with noise and a real system are used to obtain the data. We calculate autocorrelation function at the parameter values close to and away from a bifurcation. We determine that averaged peak intervals of the autocorrelation function are good indicator for predicting bifurcations.