In this paper we introdiice a new approach to the preprocessing (initial setting) of weight vectors and thus a spoed-up of the well-knowri SOM (Kohonen’s, SOFM) neural network. The idea of the method (we call it Prep through this paper) consists in spreading a small lattice over the pattern space and consequently completing its inner meshes and boundaries to obtain a larger lattice. This large lattice is then tuned by its training for a short time. To justify the speed up of the Prep method we give a detailed time analysis. To demonstrate the suggested method we show its abilities on several representative examples.