An iterative calculation method of neuron model with sigmoid function

Neural network hardware is necessary for demanding real-time applications such as pattern recognition. In the paper, an improved calculation algorithm of the neuron model with sigmoid function is proposed, which is suitable for hardware implementation. The algorithm is based on the multi dimensional binary search. The neuron circuits implemented on FPGA by the proposed algorithm have shown excellence in size and circuit frequency compared with the conventional circuits with sum of product operation.