The Partially Observed Stochastic Minimum Principle.

Abstract

The focus of this research is the filtering jump processes. To investigate the filtering of manifold valued processes, their approximation by random walks and Markov chains was studied. The object was to approximate a signal process by a finite-state jump process for which a finite dimensional filter is available. The Partially Observed Stochastic Minimum Principle: A minimum principle for a partially observed diffusion can be obtained by differentiating the statement that a control u* is optimal. The results on stochastic flows enable us to compute in an easy and explicit way the change in the cost due to a strong variation of an optical control. The only technical difficulty is the justification of the differentiation.

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Document Details

Document Type
Technical Report
Publication Date
Nov 11, 1987
Accession Number
ADA189787

Entities

People

  • John Baras
  • Michael Kohlmann
  • Robert J. Elliott

Organizations

  • University of Alberta

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  • Space

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  • Air Force
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  • Brownian Motion
  • Classification
  • Differential Equations
  • Engineering
  • Equations
  • Inequalities
  • Maryland
  • Numbers
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  • Random Variables
  • Security
  • Stochastic Control
  • Stochastic Processes
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  • Calculus or Mathematical Analysis
  • Image Processing and Computer Vision.
  • Mathematical Modeling and Probability Theory.