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http://dx.doi.org/10.6109/jkiice.2010.14.8.1759

Research on Performance Improvement of the Adaptive Active Noise Control System Using the Recurrent Neural Network  

Han, Song-Ik (동아대학교)
Lee, Tae-Oh (동아대학교)
Yeo, Dae-Yeon (동아대학교)
Lee, Kwon-Soon (동아대학교)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.14, no.8, 2010 , pp. 1759-1766 More about this Journal
Abstract
The performance of noise attenuation of the adaptive active noise control algorithm is improved using the recurrent neural network. The FXLMS that has been frequently used in the active noise control is simple and has low computational load, but this method is weak to nonlinearity of the main or secondary path since it is based on the FIR linear filter method. In this paper, the recurrent neural network filter has been developed and applied to improvement of the active noise attenuation by simulation.
Keywords
Active noise control; FIR filter; FXLMS; Recurrent neural network; Recurrent neural network; Duct system;
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