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http://dx.doi.org/10.5302/J.ICROS.2010.16.12.1220

Intelligent IIR Filter based Multiple-Channel ANC Systems  

Cho, Hyun-Cheol (Ulsan College)
Yeo, Dae-Yeon (Dong-A University)
Lee, Young-Jin (Korea Aviation Polytechnic College)
Lee, Kwon-Soon (Dong-A University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.16, no.12, 2010 , pp. 1220-1225 More about this Journal
Abstract
This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.
Keywords
active noise control; interior noise reduction; railway trains; neural network; IIR filter; secondary path model;
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Times Cited By KSCI : 2  (Citation Analysis)
Times Cited By SCOPUS : 0
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