An adaptive stochastic approximation scheme is suggested for solving a system of equations defined by functions whose values are available only through random observations on a given lattice. To improve the performance of the basic stochastic approximation scheme in the presence of outliers, the author uses isotonic and quasi-isotonic regression to fit the observed function values. The convergence of the algorithm is proved.