In this work, we consider a continuous Robbins - Monro process in a Hilbert space, a nonlinear mapping ƒ is treated instead of the usual linearity assumption. A modified process with varying truncations is analyzed, and the asymptotic properties are investigated and convergence as well as necessary and sufficient conditions are obtained. Yin and Zhu [7] considered the discrete Robbins Monro in a Hilbert space, and we extend their results to the continuous case, by introducing randomly varying truncations and we prove the almost sure convergence of the stochastic approximation algorithms.
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