DocumentCode
2966543
Title
Design and implementation of an adaptive filter using neural networks
Author
Houya, Tetsuya ; Kamata, Hiroyuki ; Ishida, Yoshihisa
Author_Institution
Dept. of Electron. & Commun., Meiji Univ., Kawasaki, Japan
Volume
1
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
979
Abstract
The LMS algorithm is generally used to design an adaptive filter. In this paper, the authors provide a new approach to designing an adaptive filter using neural networks with symmetric weights trained by the modified momentum method, which is based on the backpropagation learning algorithm. The proposed method can accelerate the computation time about 25%, in comparison with the conventional LMS method.
Keywords
adaptive filters; backpropagation; neural nets; adaptive filter; backpropagation learning algorithm; modified momentum method; neural networks; symmetric weights; Acceleration; Adaptive filters; Adaptive signal processing; Algorithm design and analysis; Application software; Artificial neural networks; Computer networks; Least squares approximation; Neural networks; Signal processing algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.714075
Filename
714075
Link To Document