Preprocessing the input patterns seems the simplest approach to invari
ant pattern recognition by neural networks. The Fourier transform has
been proposed as an appropriate and elegant preprocessor. Nevertheless
, we show in this work that the performance of this kind of preprocess
or is strongly affected by the number of stored informations. This is
so because the phase of the Fourier transform plays a more important r
ole than the amplitude in the recognition process.