In this paper, Fuzzy Neural Network (FNN) is first transformed into an equivalent fully connected three layer neural network, or FFNN. Based on the FFNN, BP training algorithm is derived to tune both the premise and consequent part of FNN. Illustrative examples are presented to check the validity of the proposed theory and algorithms. Simulation achieves satisfactory results. Developing BP training algorithm for FNN via its equivalent FFNN has its emerging values in all engineering applications using FNN, such as intelligent adaptive control, pattern recognition, and signal processing..., etc. © 2011 IEEE.