A new complex recurrent neural network equalizer for data communication

A new modified version called decision feedback complex recurrent neural network equalizer (DFCRNNE) is proposed with the study of complex recurrent neural network adaptive equalizer (CRNNE). Based on DFCRNNE, a modified real time recurrent learning (CRTRL) algorithm is developed. Simulation results show that DFCRNNE has better performance than the CRNNE based on traditional CRTRL algorithm in complex nonlinear channels with severe intersymbol interference (ISI) and nonlinear distortion.