Stochastic Perturbations and Invariant Measures of Position Dependent Random Maps via Fourier Approximations

Abstract

Let T = {τ1(x), τ2(x),…, τK(x); p1(x), p2(x),…, pK(x)} be a position dependent random map which possesses a unique absolutely continuous invariant measure [Formula: see text] with probability density function [Formula: see text]. We consider a family {TN}N≥1 of stochastic perturbations TN of the random map T. Each TN is a Markov process with the transition density [Formula: see text], where qN(x, ⋅) is a doubly stochastic periodic and separable kernel. Using Fourier approximation, we construct a finite dimensional approximation PN to a perturbed Perron–Frobenius operator. Let [Formula: see text] be a fixed point of PN. We show that [Formula: see text] converges in L1 to [Formula: see text].