Optimal Design Study of Hilbert Convertor Based on Neural-Network Algorithm

An optimal design approach of Hilbert convertor is researched in detail based on the neural-network algorithm. The main idea is to minimize the sum of the square errors between the amplitude-frequency response of the desired Hilbert convertor and that of the designed by training the weight vector of neural-network, then obtains the impulse response of Hilbert convertor. The convergence theorem of the neural-network algorithm is presented and proved, and the optimal design method is introduced by designing two kinds of Hilbert convertors. The results show that the presented optimal design approach of Hilbert convertor is significantly effective.