Logic module , in particular ASIC, in which fixed electronic circuitries are statically defined for performing neural network computation for processing data using a neural network , wherein the neural network has a plurality of first layers between an input layer and an output layer , wherein each first layer of the plurality of first layers is assigned filters , and wherein - in each first layer of the plurality of first layers , output data in the shape of linear products is generated from input data in one or more channels using filters assigned to the respective first layer of the plurality of first layers by linear computing operations, which output data is the result of convolution mathematics, and wherein the input data has one input data size per channel - for each first layer of the plurality of first layers , the sizes of receptive fields of the filters assigned to the first layers are smaller than the input data size per channel of that first layer of the plurality of first layers to which the filters are respectively assigned, and the filters perform the respective linear computing operations at different positions of the input data - in at least one first layer of the plurality of first layers , a non-linear activating function for generating output data in the shape of activation output data is applied to the output data characterised in that , with respect to the plurality of first layers present between the input layer and the output layer , - a number of filters assigned to a first layer of the plurality of first layers is equal for each of the first layers of the plurality of first layers , wherein, in each of the first layers , each of the filters assigned to a respective first layer is used for linear computing operations, - a weighting factor defining the extent to which the output of computing operations performed by the respective filter at the different positions of the input data is considered in generating the output data is assigned to each filter , - wherein the filters and their number are configured as fixed electronic circuitries in the logic module . - in each first layer of the plurality of first layers , output data in the shape of linear products is generated from input data in one or more channels using filters assigned to the respective first layer of the plurality of first layers by linear computing operations, which output data is the result of convolution mathematics, and wherein the input data has one input data size per channel - for each first layer of the plurality of first layers , the sizes of receptive fields of the filters assigned to the first layers are smaller than the input data size per channel of that first layer of the plurality of first layers to which the filters are respectively assigned, and the filters perform the respective linear computing operations at different positions of the input data - in at least one first layer of the plurality of first layers , a non-linear activating function for generating output data in the shape of activation output data is applied to the output data characterised in that , with respect to the plurality of first layers present between the input layer and the output layer , - a number of filters assigned to a first layer of the plurality of first layers is equal for each of the first layers of the plurality of first layers , wherein, in each of the first layers , each of the filters assigned to a respective first layer is used for linear computing operations, - a weighting factor defining the extent to which the output of computing operations performed by the respective filter at the different positions of the input data is considered in generating the output data is assigned to each filter , - wherein the filters and their number are configured as fixed electronic circuitries in the logic module . <EOS>