We consider random piecewise smooth, piecewise invertible maps mainly on th
e interval but also in higher dimensions. We assume that, on the average an
d possibly without any stochastic uniformity: (i) the maps expand distances
, (ii) do not have too many pieces, (iii) do not have too large a distortio
n, and (iv) are strongly mixing. We assume no Markov property. We prove tha
t as in the classical case of the iteration of a fixed piecewise expanding
map of the interval, we have exponential decay of random correlations. Our
proof builds on the one given by C. Liverani for deterministic, mixing and
piecewise expanding interval maps.
We demand very little of the stochastic process giving the maps. In particu
lar, if the maps are beta-transformations on [0, 1[(d), i.e., x(n+1) = B(n1)x(n) mod Z(d) with B-n:R-d --> Rd affine, then our results apply to ail s
tationary and ergodic processes B-1, B-2,... which expand on the average an
d satisfy the mixing condition above.
We remark that our setting does not imply fast decay of integrated correlat
ions.