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Robust Recursive Bayesian Estimation and Quantum Minimax Strategies

  • P. Pardalos
  • V. Yatsenko
  • S. Butenko
Chapter
Part of the Applied Optimization book series (APOP, volume 66)

Abstract

The problem of a recursive realization of Bayesian estimation for incomplete experimental data is considered. A differential-geometric structure of nonlinear estimation is studied. It is shown that the use of a rationally chosen description of the true posterior density produces a geometrical structure defined on the family of possible posteriors. Pythagorean-like relations valid for probability distributions are presented and their importance for estimation under reduced data is indicated. A robust algorithm for estimation of unknown parameters is proposed, which is based on a quantum implementation of the Bayesian estimation procedure.

Key words

Bayesian estimation robust estimation control optimization quantum detection model approximation 

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Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • P. Pardalos
    • 1
  • V. Yatsenko
    • 2
  • S. Butenko
    • 3
  1. 1.Center for Applied Optimization, Dept. of Industrial and Systems EngineeringUniversity of FloridaUSA
  2. 2.Scientific Foundation of Researchers and Specialists on Molecular Cybernetics and InformaticsUSA
  3. 3.Dept. of Industrial and Systems EngineeringUniversity of FloridaUSA

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