Online estimation of complexity using variable forgetting factor

Author

Sugisaki, Koichi ; Ohmori, Hiromitsu

Author_Institution

Keio Univ., Tokyo

fYear

2007

fDate

17-20 Sept. 2007

Firstpage

1

Lastpage

6

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;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE, 2007 Annual Conference

Conference_Location

Takamatsu

Print_ISBN

978-4-907764-27-2

Electronic_ISBN

978-4-907764-27-2

Type

conf

DOI

10.1109/SICE.2007.4420939

Filename

4420939