Slow stochastic approximation processes are good for estimating slope

A continuous-time Robbins–Monroe process violating the conditions necessary for the CLT to hold will be considered. It will be shown that although the estimator process 6% converges to the root to be determined a.s. it is sufficiently rich to get strong consistent estimator of the slope of the regressor function using noisy observations of the regressor function at $\theta_t-s$ only.