Stochastic convergence properties of the adaptive gradient lattice

A stochastic fixed-point theorem is used as a basis for the study of stochastic convergence properties (in mean-squares sense) of the adaptive gradient lattice filter. Such properties include conditions on the stepsize in the adaptive algorithm and analytic expressions for the misadjustment and convergence rate.