Design and Implementation of an Adaptive Filter Using Neural Networks

Tetsuya Hoya, Hiroyuki Kamata, Yoshihisa Ishida

Published: 24 Oct 1993, Last Modified: 04 May 2025Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan)EveryoneCC BY 4.0

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.