Feed-Forward Neural Network Blind Equalization Algorithm Based on Super-Exponential Iterative

In order to overcome the slow convergence rate and larger mean square error of feed-forward neural network (FNN) blind equalization algorithm, a feed-forward neural network blind equalization algorithm based on super-exponential iterative (SEI) is proposed, on basis of the futures of super-exponential iterative and feed-forward neural network blind equalization algorithm. The proposed algorithm has ability to improve convergence rate and to reduce mean square error via full using the whiten ability of SEI. With underwater acoustic channels simulation results show that the proposed algorithm has outperformed feed-forward neural network (FNN) blind equalization algorithm in the convergence rate and mean square error.