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Blind equalization by neural network has two difficult problems, which is convergence rate and computational complexity. Resilient BP algorithm (RPROP) combining compressed transfer function is proposed to improve blind equalization by neural network. Compressed transfer function can make the input signal avoid saturation zone and RPROP algorithm can improve convergence rate effectively without adding additional calculation amount. The effectiveness of the algorithm is identified by simulation.