Buch, Englisch, Band 34, 385 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 610 g
Buch, Englisch, Band 34, 385 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 610 g
Reihe: Stochastic Modelling and Applied Probability
ISBN: 978-3-642-08175-0
Verlag: Springer
An up-to-date, self-contained review of a wide range of recursive methods for stabilization, identification and control of complex stochastic models (guiding a rocket or a plane, organizing multi-access broadcast channels, self-learning of neural networks.). Suitable for mathematicians (researchers and also students) and engineers.
Zielgruppe
Research
Fachgebiete
Weitere Infos & Material
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.