A Blind Equalization Algorithm Based on Dynamic Fuzzy Neural Network

The research of blind equalization algorithm based on the dynamic fuzzy neural network (DFNN) is proposed in this paper. The DFNN possesses characteristics such as dynamic mapping and restraint noise. The blind equalization is the process of dynamic equalization essentially because digital communication channel is time-varying and indeterminate. The algorithm proposed in this paper accords with the dynamic characteristic of channel because it uses current data and history data. Hence, the new algorithm possesses distinct advantages of stability, convergence speed and convergence properties over the traditional neural network (NN) blind equalization algorithm. The improved performance of the proposed models is confirmed through computer simulations.