Decentralized parameter estimation with fuzzy information

V. N S Samarasooriya, Pramod Kumar Varshney

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

Abstract

The use of fuzzy sets in representing uncertainty in signal detection and estimation problems has been shown to complement the conventional approaches using probabilistic modeling. We concentrate on an approach, where the sample information available from the physical phenomenon of interest is assumed to be vague. We study and analyze a parameter estimation scheme in a decentralized system when the data available at each sensor is vague. The vagueness of the data is represented by means of `fuzzy events' defined over the real line. The optimum global estimator in a minimum mean square error sense is obtained, and the corresponding optimum partitioning of the fuzzy information space is presented. We also discuss a suboptimum data partitioning method using the Fisher information measure.

Original languageEnglish (US)
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
PublisherIEEE Computer Society
Pages142-147
Number of pages6
StatePublished - 1997
EventProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97 - Syracuse, NY, USA
Duration: Sep 21 1997Sep 24 1997

Other

OtherProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97
CitySyracuse, NY, USA
Period9/21/979/24/97

ASJC Scopus subject areas

  • Computer Science(all)
  • Media Technology

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    Samarasooriya, V. N. S., & Varshney, P. K. (1997). Decentralized parameter estimation with fuzzy information. In Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS (pp. 142-147). IEEE Computer Society.