On the strong stability of ergodic iterations

Miklós Rásonyi, Attila Lovas, László Györfi

Abstract: We revisit processes generated by iterated random functions driven by a stationary and ergodic sequence. Such a process is called strongly stable if a random initialization exists, for which the process is stationary and ergodic, and for any other initialization, the difference of the two processes converges to zero almost surely. Under some mild conditions on the corresponding recursive map, without any condition on the driving sequence, we show the strong stability of iterations. Several applications are surveyed such as stochastic approximation and queuing. Furthermore, new results are deduced for Langevin-type iterations with dependent noise and for multitype branching processes.

Mathematics Subject Classification ID

Stationary stochastic processes (60G10) Random iteration (37H12)

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