Method for computer-aided learning of a neural network and neural network

There is described a method for computer-aided learning of a neural network, with a plurality of neurons in which the neurons of the neural network are divided into at least two layers, comprising a first layer and a second layer crosslinked with the first layer. In the first layer input information is respectively represented by one or more characteristic values from one or several characteristics, wherein every characteristic value comprises one or more neurons of the first layer. A plurality of categories is stored in the second layer, wherein every category comprises one or more neurons of the second layer. For one or several pieces of input information, respectively at least one category in the second layer is assigned to the characteristic values of the input information in the first layer. Input information is entered into the first layer and subsequently at least one state variable of the neural network is determined and compared to the at least one category of this input information assigned in a preceding step. The crosslinking between the first and second layer is changed depending on the comparison result from a preceding step.