Application of decision feedback recurrent neural network with real-time recurrent algorithm

The recurrent neural network is a kind of neural network with one or more feedback loops. We may have feedback from the output neurons of the multilayer to the input layer. Yet another possible form of feedback is from the hidden neurons of the network to the input layer. In this paper, we propose a channel equalization scheme using a decision feedback recurrent neural network, which has feedback loops from both the hidden layer and the decision part, with real-time recurrent network. Simulation results show that the proposed scheme outperforms the recurrent neural network that only has feedbacks loops from the hidden layer