Sufficient Statistics for Decentralized Estimation,

Abstract

Decentralized estimation problems involve several agents receiving separate noisy observations of a common stochastic process, and each seeks to generate a local estimate of the state of that process. In the general case, these estimates are desired to be consistent in some way, and thus may be jointly penalized with the state via a cost functional to be minimized. In many cases, each agent need only keep track of its local conditional state probability distribution in order to general the optimal estimates. This paper examines the boundary between problems where this statistic is sufficient and those where it is not; when it is not, the additional information which must be kept appears to have additional structure as illustrated by an example. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1982
Accession Number
ADA124941

Entities

People

  • Robert R. Tenney

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Computations
  • Computer Programming
  • Covariance
  • Detectors
  • Dynamic Programming
  • Dynamics
  • Engineering
  • Estimators
  • Feedback
  • Filtration
  • Information Processing
  • Optimization
  • Probability
  • Probability Distributions
  • Random Variables
  • Sequences
  • Transitions

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.