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Please use this identifier to cite or link to this item: http://idr.iitbbs.ac.in/jspui/handle/2008/630
Title: An improved Filtered-x Least Mean Square algorithm for acoustic noise suppression
Authors: Kar A.
Chanda A.P.
Mohapatra S.
Chandra M.
Keywords: Active noise control
Adaptive filter
FXLMS
Least Mean Square
Mean Square Error
Issue Date: 2014
Citation: 7
Abstract: In the modern age scenario noise reduction is a major issue, as noise is responsible for creating disturbances in day-to-day communication. In order to cancel the noise present in the original signal numerous methods have been proposed over the period of time. To name a few of these methods we have noise barriers and noise absorbers. Noise can also be suppressed by continuous adaptation of the weights of the adaptive filter. The change of weight vector in adaptive filters is done with the help of various adaptive algorithms. Few of the basic noise reduction algorithms include Least Mean Square algorithm, Recursive Least Square algorithm etc. Further we work to modify these basic algorithms so as to obtain Normalized Least Mean Square algorithm, Fractional Least Mean Square algorithm, Differential Normalized Least Mean Square algorithm, Filtered-x Least Mean Square algorithm etc. In this paper we work to provide an improved approach for acoustic noise cancellation in Active Noise Control environment using Filtered-x LMS (FXLMS) algorithm. A detailed analysis of the algorithm has been carried out. Further the FXLMS algorithm has been also implemented for noise cancellation purpose and the results of the entire process are produced to make a comparison. � Springer International Publishing Switzerland 2014.
URI: http://dx.doi.org/1007/978-3-319-07353-8_4
http://10.10.32.48:8080/jspui/handle/2008/630
Appears in Collections:Research Publications

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