Online estimation of complexity using variable forgetting factor

Koichi Sugisaki, Hiromitsu Ohmori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

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 additon, 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.

Original languageEnglish
Title of host publicationSICE Annual Conference, SICE 2007
Pages1-6
Number of pages6
DOIs
Publication statusPublished - 2007 Dec 1
EventSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
Duration: 2007 Sep 172007 Sep 20

Publication series

NameProceedings of the SICE Annual Conference

Other

OtherSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
CountryJapan
CityTakamatsu
Period07/9/1707/9/20

Keywords

  • Approximate entropy
  • Complexity
  • Forgetting factor
  • Online
  • Recursive
  • Sample entropy

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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