An invariance principle for a finite dimensional stochastic approximation method in a Hilbert space

For the application of the classical Robbins-Monro procedure in a Hilbert space the statistician generally has to observe infinite dimensional vectors. A modified procedure is proposed, which works in appropriate finite dimensional subspaces of growing dimension. For this procedure an invariance principle is given together with some applications.