Random Iterative Models - Stochastic Modelling and Applied Probability Softcover reprint of hardcover 1st ed. 1997 edition

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.