Enhanced neural filter design and its application to the active control of nonlinear noise

Authors:
Cheng-Yuan Chang;I-Ling Chung;Chang-Min Chou;Fuh-Hsin Hwang
Affiliations:
Department of Electronic Engineering, Ching Yun University, Jhongli City, Taiwan, R.O.C.;Department of Electronic Engineering, Ching Yun University, Jhongli City, Taiwan, R.O.C.;Department of Electronic Engineering, Ching Yun University, Jhongli City, Taiwan, R.O.C.;Department of Optoelectronics and Communication Engineering, National Kaohsiung Normal University, Kaohsiung County, Taiwan, R.O.C.
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

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Abstract

A novel neural filter and its application to active control of nonlinear noise are proposed in this paper. This method helps to avoid the premature saturation of backpropagation algorithm; meanwhile, guarantees the system convergence by the proposed self-tuning method. The comparison between the conventional filtered-X least-mean-square (FXLMS) algorithm and proposed method for nonlinear broadband noise in active noise cancellation (ANC). system is also made in this paper. The proposed design method is very easy to be implemented and versatile to the other applications. Several simulation results show that the proposed method can effectively cancel the narrowband and nonlinear broadband noise in a duct.