Abstract: This paper studies the influence of activation functions in BP algorithms, and comes to a conclusion: The more cliffy the function is ,the quicker the convergence of the algorithm. A new method in BP algorithm is proposed in order to avoid local minimum, that is, add trainning data step by step.