This paper presents analytical, numerical, and experimental results for a s
tochastic gradient adaptive scheme th:at identifies a polynomial-type nonli
near system with memory for noisy output observations, The analysis include
s the computation of the stationary points, the mean square error surface,
and the stability regions of the algorithm for Gaussian data, Convergence o
f the mean is studied using L-2 and Euclidian norms, Monte Cal lo simulatio
ns confirm the theoretical predictions that show a small sensitivity to the
observation noise. An application is presented for the identification of a
nonlinear time-delayed feedback system.