Bayesian Sensory Information Processing

  • 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

The introductory chapter addressed the need for the application of constraints, both natural and artificial, to aid in the performance of sensory information processing tasks. We saw that a major problem concerning the use of constraints lies in determining how the constraints are to be embedded in the algorithm(s) that carry out the information processing tasks.

Keywords

Kalman Filter Data Fusion Sensor Noise Subjective Approach Recursive Filter 
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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