Analysis of Momentum Factor in Neural Network Blind Equalization Algorithm

In this paper, the principle of neural network blind equalization algorithm was depicted, the fault of traditional BP (back propagation) algorithm, which is slow convergence rate and easy to fall into a local minimum, was analyzed, the influence of momentum factor to equalization performance was researched, the convergence track of traditional BP algorithm and momentum factor BP algorithm was compared. From the above, we can see the new algorithm can avoid effectively a local minimum and speed up the convergence rate. On this basis, three-layer forward neural network was adopted, the iteration equation of neural network blind equalization algorithm based on momentum factor was deduced. The computer simulation results show the effectiveness of the new algorithm.