1. A method for determining state parameters of a chemical reactor with a plurality of neural networks having n inputs and m outputs comprising the steps of: bringing the chemical reactor out of a stationary state; measuring quantities from the chemical reactor in a phase wherein the chemical reactor oscillates back into the stationary state; determining from the measured quantities a sequence of measured quantities (z.sub.k (t.sub.j); k=1. .. m) for the chemical reactor where t.sub.j (j=1. .. s) is a point in time at which the sequence of measured quantities (z.sub.k (t.sub.j)) was determined; generating a plurality of individual curves in normal coordinates (.xi..sub.i ; l=1. .. n) with individual ones of a plurality data generators based on a predetermined normal form that describes a critical state of the chemical reactor; allocating the plurality of neural networks (NNb) respectively in one-to-one correspondence to the data generators and applying the curves in normal coordinates to the neural networks; wherein each neural network is adapted to the sequence of measured quantities (z.sub.k (t.sub.j)) with a parameter optimization method; and determining and processing a parameter which represents the state parameters of the chemical reactor based an the neural network which is selected in light of the parameter optimization.