  We present a perfect simulation algorithm for stationary processes indexed by
Z, with summable memory decay. Depending on the decay, we construct the process
on finite or semi-infinite intervals, explicitly from an i.i.d. uniform
sequence. Even though the process has infinite memory, its value at time 0
depends only on a finite, but random, number of these uniform variables. The
algorithm is based on a recent regenerative construction of these measures by
Ferrari, Maass, Mart{\'\i}nez and Ney. As applications, we discuss the perfect
simulation of binary autoregressions and Markov chains on the unit interval.
