Neural Network Blind Equalization Algorithm Based on Feed Forward Neural Network
- Huiqing Zhao
- Corresponding Author
- Huiqing Zhao
Available Online March 2015.
- https://doi.org/10.2991/iset-15.2015.31How to use a DOI?
- Neural network, Blind equalization algorithm, Feed-forward, Cost functions convergence
- 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.
- 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 SN - 2352-538X UR - https://doi.org/10.2991/iset-15.2015.31 DO - https://doi.org/10.2991/iset-15.2015.31 ID - Zhao2015/03 ER -