A Novel Variable Step Size LMS Algorithm Based On Neural Network
Authors
Anyang Zhang1, Ningsheng Gong
1College of Information Science and Engineering, Nanjing University of Technology
Corresponding Author
Anyang Zhang
Available Online October 2007.
- DOI
- 10.2991/iske.2007.76How to use a DOI?
- Keywords
- adapt filtering, variable step size LMS algorithm, BP neural network, prior knowledge
- Abstract
This paper presents a new variable step size LMS algorithm based on neural network (BP-LMS). A non-linear relationship amongst the input vectors, deviation errors and the learning steps is constructed by BP model, which is employed to determine the learning steps during adaptive processing. The proposed algorithm also takes the prior knowledge into the LMS algorithm. Simulation experiments suggest that BP-LMS algorithm is capable of decreasing the time of convergent progress rapidly and satisfactory performance is attainable even with the presence of high level of noise.
- Copyright
- © 2007, 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/).
Cite this article
TY - CONF AU - Anyang Zhang AU - Ningsheng Gong PY - 2007/10 DA - 2007/10 TI - A Novel Variable Step Size LMS Algorithm Based On Neural Network BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 454 EP - 458 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.76 DO - 10.2991/iske.2007.76 ID - Zhang2007/10 ER -