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Weakly vs. Strongly Coupled Data Fusion: A Classification of Fusional Methods

  • James J. Clark
  • Alan L. Yuille
Chapter
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 105)

Abstract

Chapter 2 introduced the Bayesian approach to the processing of sensory information. One of the notable aspects of the Bayesian formulation is the ease with which constraints can be embedded. The constraint embedding was seen to be performed through the specification of suitable image formation and prior models. The image formation model typically involved the physical, and to a lesser extent natural, constraints, while the prior model typically involved natural and artificial constraints.

Keywords

Kalman Filter Sensory Module Data Fusion FUSIONAL Method Prior Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1990

Authors and Affiliations

  • James J. Clark
    • 1
  • Alan L. Yuille
    • 1
  1. 1.Division of Applied SciencesHarvard UniversityCambridgeUSA

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