Abstract
ABSTRACTIn this article, we study a stochastic approximation algorithm that approximates the exact root θ of a function M defined in ℝd into ℝd. The function M cannot be known exactly, but only noisy measurements are available at each point xn with the error ξn. The sequence of noise (ξn)n is random; we treat both cases where it is independent and dependent and we establish the complete convergence of the approximated sequence of θ.
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