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Probabilistic Inference in Signal Processing

  • Joseph J. K. Ó Ruanaidh
  • William J. Fitzgerald
Part of the Statistics and Computing book series (SCO)

Abstract

In this chapter, the fundamental concepts and techniques underlying Bayesian inference are reviewed. We begin with a definition of the key problem of data analysis, which is to interpret data in the presence of noise. We advocate a Bayesian approach to this problem.

Keywords

General Linear Model Likelihood Function Prior Probability Posterior Density Nuisance Parameter 
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 1996

Authors and Affiliations

  • Joseph J. K. Ó Ruanaidh
    • 1
  • William J. Fitzgerald
    • 1
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK

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