Blind Equalization Algorithm Based on Compensation Fuzzy Neural Network

Blind equalization based on compensation fuzzy neural network has proposed. It using compensation neurons to get tradeoff between negative and active operation, thus the network can be training using fuzzy rule of initial right or wrong setting, and fault tolerance and stability are improved. Simulations results show that this algorithm has faster convergence speed and less residual error compared to the in here algorithm, and the blind equalization performance is improved effectively.