1. A method of analyzing operation of a multistage compressor of a gas turbine including a plurality of compressor stages, wherein a neural network is trained based upon normal operation of the gas turbine, comprising: measuring a dynamic pressure signal by a pressure sensor in or on the multistage compressor; measuring an operating parameter of the gas turbine by a further sensor during normal operation of the gas turbine; performing a frequency analysis of the dynamic pressure signal, wherein a parameter of a frequency spectrum of the pressure signal is determined; training a neural network based upon the measured operating parameter and the parameter of the frequency spectrum of the pressure signal, wherein the measured operating parameter and the parameter of the frequency spectrum of the pressure signal are input variables, and wherein a diagnosis characteristic value representing a probability measure of a presence of normal operation of the gas turbine as a function of the input variables is an output variable; determining a characteristic frequency band based upon a rotation speed of the gas turbine and a number of guide vanes and rotor blades in the relevant compressor stage as a parameter of the frequency spectrum for each compressor stage; and calculating for each characteristic frequency band an energy component of the pressure signal contained therein, the energy component being used as input variable for the neural network.