Design of the adaptive noise canceler using neural network with backpropagation algorithm

Author

Chu, Hyung Suk ; An, Chong Koo

Author_Institution

DSP Lab., Ulsan Univ., South Korea

Volume

2

fYear

1999

fDate

1999

Firstpage

762

Abstract

In this paper, an adaptive noise canceller using a neural network with backpropagation is designed. The adaptive noise canceller using the least mean square algorithm has the large correlativity of the reference signal and shows the limitation of the big signal to noise ratio. The system proposed in this paper plays an important role in denoising these signals. In addition, the experiments are carried out to analyze the effects of the number of hidden layers and nodes about the system. The performance of the proposed adaptive noise canceller is compared with that of the system which is used the least mean square algorithm

Keywords

acoustic signal processing; active noise control; adaptive control; backpropagation; control system synthesis; neurocontrollers; adaptive noise canceller design; backpropagation algorithm; hidden layers; hidden nodes; least mean square algorithm; neural network; signal denoising; signal to noise ratio; Adaptive filters; Adaptive signal processing; Algorithm design and analysis; Backpropagation algorithms; Least mean square algorithms; Neural networks; Noise cancellation; Signal processing; Signal processing algorithms; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Science and Technology, 1999. KORUS '99. Proceedings. The Third Russian-Korean International Symposium on

Conference_Location

Novosibirsk

Print_ISBN

0-7803-5729-9

Type

conf

DOI

10.1109/KORUS.1999.876276

Filename

876276