A Novel Variable Step Size LMS Algorithm Based On Neural Network

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/).

Download article (PDF)

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  -