Published online by Cambridge University Press: 14 July 2016
Let V be a countably infinite set, and let {Xn, n = 0, 1, ·· ·} be random vectors in which satisfy Xn = AnXn – 1 + ζn , for i.i.d. random matrices {An } and i.i.d. random vectors {ζ n }. Interpretation: site x in V is occupied by Xn (x) particles at time n; An describes random transport of existing particles, and ζ n (x) is the number of ‘births' at x. We give conditions for (1) convergence of the sequence {Xn } to equilibrium, and (2) a central limit theorem for n–1/2(X 1 + · ·· + Xn ), respectively. When the matrices {An } consist of 0's and 1's, these conditions are checked in two classes of examples: the ‘drip, stick and flow model' (a stochastic flow with births), and a neural network model.