Title :
Design of an adaptive FIR filter using symmetric neural networks
Author :
Houya, Tetsuya ; Kamata, Hiroyuki ; Ishida, Yoshihisa
Author_Institution :
Dept. of Electron. & Commun., Meiji Univ., Kawasaki, Japan
Abstract :
The LMS algorithm is generally used to design an adaptive filter. In this paper, the authors provide a new approach to design 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 15%, in comparison with the conventional LMS method
Keywords :
adaptive filters; backpropagation; digital filters; filtering and prediction theory; neural nets; LMS algorithm; adaptive FIR filter; backpropagation learning algorithm; modified momentum method; symmetric neural networks; symmetric weights; Adaptive filters; Additive noise; Artificial neural networks; Finite impulse response filter; Interference cancellation; Least squares approximation; Neural networks; Noise cancellation; Signal processing; Signal processing algorithms;
Conference_Titel :
Electrical and Computer Engineering, 1993. Canadian Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1993.332227
