Neural Network Blind Equalization Algorithm Based on Feed Forward Neural Network

DOI

10.2991/iset-15.2015.31How to use a DOI?

Keywords

Neural network, Blind equalization algorithm, Feed-forward, Cost functions convergence

Abstract

Existing neural network algorithms have the problems of slow convergence and low accuracy. In response to this phenomenon, this paper presents a neural network blind equalization algorithm based on feed-forward neural network. And we proposed feed-forward neural network blind equalization algorithm by research of traditional neural network blind equalization algorithm. And it is using a feed-forward neural network of the hidden layer to approximate the objective function. At last, we by combining the cost functions of feed-forward network to correct the acquired information. Experimental results show that the experimental results basically consistent with the expected results. By comparison with other algorithms, this algorithm has better convergence and accuracy.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huiqing Zhao
PY  - 2015/03
DA  - 2015/03
TI  - Neural Network Blind Equalization Algorithm Based on Feed Forward Neural Network
BT  - Proceedings of the First International Conference on Information Science and Electronic Technology
PB  - Atlantis Press
SP  - 121
EP  - 124
SN  - 2352-538X
UR  - https://doi.org/10.2991/iset-15.2015.31
DO  - 10.2991/iset-15.2015.31
ID  - Zhao2015/03
ER  -