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E C E 830: Estimation and Decision Theory

  • Catalog Description:
    Estimation and decision theory applied to random processes and signals in noise: Bayesian, maximum likelihood, and least squares estimation; the Kalman filter; maximum likelihood and maximum aposteriori detection; adaptive receivers for channels with unknown parameters or dispersive, fading characteristics; the RAKE receiver; detection systems with learning features.
  • Credits: 3
  • Prerequisites: ECE 730 or equiv
  • Official Course Description (pdf)