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,...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Karny, Miroslav (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Colección:Advanced Information and Knowledge Processing,
Temas:
Computer science.
User interfaces (Computer systems).
Human-computer interaction.
Artificial intelligence.
Computer simulation.
Pattern recognition systems.
Mathematical statistics-Data processing.
Models of Computation.
User Interfaces and Human Computer Interaction.
Artificial Intelligence.
Computer Modelling.
Automated Pattern Recognition.
Statistics and Computing.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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