A multidimensional adaptive stochastic approximation procedure trun-cated at randomly varying bounds is studied for the regression function observedwith correlated noise.The algorithm is proved to be asymptotically efficient.Theresult of the paper generalizes the one shown in[1]for the observation noise be-ing i.i.d.random vectors and under other restrictive conditions imposed on theregression function.
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