Statistical Properties of the Integral of a Binary Random Process

Abstract

Statistical properties of the output z(t) of a finite time integrator are discussed. The input considered is a binary random y(t) having successive axis-crossing intervals which are statistically independent. Transform expressions are derived for the first- and second-order transition probability densities of the integrated process, and it is shown how these results may be extended to three or more dimensions. Four processes are considered as examples. The integrated z(t) is shown to be a projection of a Markov in three dimensions. The other two components are the original binary y(t) , and an associated ramp process x(t) . Various statistical properties of this ramp are considered and it is shown that x(t) is Markovian in one dimension. The first-order probability density and the transition probability density are discussed. Also, the transition probability density for the joint [x(t), y(t), z(t)] is given. Finally, in Appendix II, results are given for the first passage and recurrence time probability densities of x(t) , together with a relation between these two density functions.