Synthetical backpropagation algorithm

The paper presents a synthetical backpropagation algorithm (SBP) for multilayer feedforward neural networks. The general ability, speed of training, and global optimal solution are considered in SBP. A new generalized error index function is used in SBP. The backpropagation technique based on searching output space is proposed and used in SBP. SBP has a dynamical adaptive regulation learning rate, a variable momentum coefficient and ability of self regulation activate characteristic. The contrast experiments indicate that SBP has a faster convergence speed than BP and can achieve a global optimal solution