Elman's recurrent neural networks using resilient back propagation for harmonic detection

Abstract

In this study, the method to apply the Elman's recurrent neural networks using resilient back propagation for harmonic detection is described. The feed forward neural networks are also used for comparison. The distorted wave including 5th, 7th, 11th, 13th harmonics were simulated and used for training of the neural networks. The distorted wave including up to 25th harmonics were prepared for testing of the neural networks. Elman's recurrent and feed forward neural networks were used to recognize each harmonic. The results obtained using Elman's recurrent neural networks are better than the results values obtained using the feed forward neural networks for resilient back propagation. © Springer-Verlag Berlin Heidelberg 2004.