The invention relates to a method for calculating a neuron layer of a multi-layer perceptron model, comprising a hardwired calculation core (11, 13, 14) formed in a hardware for calculating a fixedly preset computing algorithm in coupled functional blocks, wherein a neuron (20) of a neuron layer of the perceptron model is calculated using an activation function, wherein the activation function corresponds to a simplified sigmoid function and a simplified tanh function, the activation function being formed by zero-point mirroring of the negative definition range of the exponential function.
METHOD FOR CALCULATING A NEURON LAYER OF A MULTI-LAYER PERCEPTRON MODEL WITH SIMPLIFIED ACTIVATION FUNCTION