Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.