Title :
Online estimation of complexity using variable forgetting factor
Author :
Sugisaki, Koichi ; Ohmori, Hiromitsu
Author_Institution :
Keio Univ., Tokyo
Abstract :
Recently, the utility of sample entropy (SampEn) as a complexity measure was shown via applying to time series data generated from in a variety of systems. However, online estimation method of SampEn index has not been developed yet. If SampEn can be estimated online, we can apply this index to time-varying system. In this paper, we developed the recursive SampEn algorithm to estimate the changes of system complexity online. In addition, we verified the utility of this algorithm by simulations. Consequently, we assure that this algorithm can be applied to time series generated from in a variety of time-varying system potentially.
Keywords :
recursive estimation; time series; time-varying systems; online estimation method; recursive SampEn algorithm; sample entropy; system complexity; time series; time-varying system; variable forgetting factor; Biological systems; Biomedical monitoring; Data engineering; Design engineering; Entropy; Recursive estimation; Statistics; Systems engineering and theory; Time measurement; Time varying systems; Approximate Entropy; Sample Entropy; complexity; forgetting factor; online; recursive;
Conference_Titel :
SICE, 2007 Annual Conference
Conference_Location :
Takamatsu
Print_ISBN :
978-4-907764-27-2
Electronic_ISBN :
978-4-907764-27-2
DOI :
10.1109/SICE.2007.4420939
