Optimized Bayesian Dynamic Advising Theory and Algorithms.

Written by one of the world’s leading groups in the area of Bayesian identification, control and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. Starting from abstract ideas and formulations, and culminating in detailed algorithms, Optim...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: London : Springer London, 2006.
Σειρά:Advanced Information and Knowledge Processing
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Underlying theory
  • Approximate and feasible learning
  • Approximate design
  • Problem formulation
  • Solution and principles of its approximation: learning part
  • Solution and principles of its approximation: design part
  • Learning with normal factors and components
  • Design with normal mixtures
  • Learning with Markov-chain factors and components
  • Design with Markov-chain mixtures
  • Sandwich BMTB for mixture initiation
  • Mixed mixtures
  • Applications of the advisory system
  • Concluding remarks.