A Novel VSS-EBP Algorithm Based on Adaptive Variable Learning Rate

One of the most significant parameter in increasing the efficiency of MLP NN that utilizes the EBP algorithm for training network is convergence speed which different methods have been proposed for improving it. In this paper, we use a variable learning rate method for increasing the convergence speed of EBP algorithm, which its idea have come from a one way presented to improve the efficiency of Standard LMS. The result of comparison of standard EBP and proposed VSSEBP algorithm over various datasets demonstrate that VSSEBP have high convergence speed. All experiments have performed on noisy data with various SNR values.