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  4. Collaborative adaptive exponential linear-in-the-parameters nonlinear filters
 
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Collaborative adaptive exponential linear-in-the-parameters nonlinear filters

Source
25th European Signal Processing Conference Eusipco 2017
Date Issued
2017-10-23
Author(s)
Patel, Vinal
Pradhan, Somanath
George, Nithin V.  
DOI
10.23919/EUSIPCO.2017.8081700
Volume
2017-January
Abstract
An adaptive exponential functional link artificial neural network (AEFLANN) based active noise control (ANC) system trained using a collaborative learning scheme has been designed in this paper. In the proposed approach, separate learning mechanism is used for updating the weights of the linear portion of the AEFLANN and its non-linear section. The outputs of the linear and non-linear sections are suitably combined and the update mechanism involves the update of weights of linear and non-linear portions, the combination parameter and the adaptive exponential factor. Simulation study shows enhanced noise cancellation in comparison with other non-linear ANC schemes compared.
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URI
https://d8.irins.org/handle/IITG2025/23009
Subjects
Active noise control | Functional link artificial neural network | Noise cancellation | Non-linear filter
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