Proceedings of the First International Conference on Information Science and Electronic Technology

Neural Network Blind Equalization Algorithm Based on Feed Forward Neural Network

Authors
Huiqing Zhao
Corresponding Author
Huiqing Zhao
Available Online March 2015.
DOI
https://doi.org/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.
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Proceedings
First International Conference on Information Science and Electronic Technology (ISET 2015)
Part of series
Advances in Computer Science Research
Publication Date
March 2015
ISBN
978-94-62520-50-9
DOI
https://doi.org/10.2991/iset-15.2015.31How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Huiqing Zhao
PY  - 2015/03
DA  - 2015/03
TI  - Neural Network Blind Equalization Algorithm Based on Feed Forward Neural Network
BT  - First International Conference on Information Science and Electronic Technology (ISET 2015)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/iset-15.2015.31
DO  - https://doi.org/10.2991/iset-15.2015.31
ID  - Zhao2015/03
ER  -