Blind Equalization Algorithm based on Fuzzy Neural Network in QAM System

A new blind equalization algorithm based on fuzzy neural network classifier was proposed. It was applied in the QAM System. Channel estimation and fuzzy neural network classifier are combined to carry out blind equalization. The primary signal was attained by de-convolution. Judgment range of fuzzy neural network was adjusted dynamically by competition study algorithm, and then blind equalization was realized. Simulations illuminate that the new algorithm improves convergence speed and reduces residual error and BER (Bit Error Ratio).