Multilayer perceptron neural networks for active noise cancellation

Author

Chen, Casper K. ; Chiueh, Tzi-Dar

Author_Institution

Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan

Volume

3

fYear

1996

fDate

12-15 May 1996

Firstpage

523

Abstract

Some experiment results of multilayer perceptron neural networks for active noise cancellation (ANC) are presented in this paper. Active noise cancellation is an approach to noise reduction in which a secondary noise source destructively interferes with the unwanted noise. Conventional ANC systems apply a digital filter to cancel the noise and suffer from the fact that each noisy environment needs to be treated individually. In this paper, we introduce a three-layer MLP neural network to replace the aforementioned filter. We apply this architecture to three different broad-band-noise environments and achieve 20 dB noise attenuation

Keywords

acoustic noise; acoustic signal processing; active noise control; multilayer perceptrons; acoustic noise attenuation; active noise cancellation; broadband-noise environments; multilayer perceptron neural networks; secondary noise source; three-layer MLP network; Acoustic noise; Active noise reduction; Finite impulse response filter; Low-frequency noise; Magnetic noise; Multi-layer neural network; Multilayer perceptrons; Neural networks; Noise cancellation; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on

Conference_Location

Atlanta, GA

Print_ISBN

0-7803-3073-0

Type

conf

DOI

10.1109/ISCAS.1996.541648

Filename

541648