On Stochastic Stability of a Class of non-Markovian Processes and Applications in Quantization
arXiv:1612.06988 · doi:10.1137/140984154
Abstract
In many applications, the common assumption that a driving noise process affecting a system is independent or Markovian may not be realistic, but the noise process may be assumed to be stationary. To study such problems, this paper investigates stochastic stability properties of a class of non-Markovian processes, where the existence of a stationary measure, asymptotic mean stationarity and ergodicity conditions are studied. Applications in feedback quantization and stochastic control are presented.
A clarification in the statement of Theorem 3.9 (on Assumption 2.3 for the applications)