Random Iterative Models /

The recent development of computation and automation has lead to quick advances in the theory and practice of recursive methods for stabilization, identification and control of complex stochastic models (guiding a rocket or a plane, orgainizing multiaccess broadcast channels, self-learning of neural...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Duflo, Marie
Format: Electronic eBook
Language:Inglés
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 1997.
Series:Stochastic modelling and applied probability ; 34.
Subjects:
Mathematics.
Algorithms.
Distribution (Probability theory)
Computer algorithms.
Mathématiques.
Algorithmes.
Distribution (Théorie des probabilités)
mathematics.
applied mathematics.
algorithms.
distribution (statistics-related concept)
Computer algorithms
Algorithms
Mathematics
Online Access:Texto completo
Table of Contents:
  • I. Sources of Recursive Methods
  • 1. Traditional Problems
  • 2. Rate of Convergence
  • 3. Current Problems
  • II. Linear Models
  • 4. Causality and Excitation
  • 5. Linear Identification and Tracking
  • III. Nonlinear Models
  • 6. Stability
  • 7. Nonlinear Identification and Control
  • IV. Markov Models
  • 8. Recurrence
  • 9. Learning.

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