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Please use this identifier to cite or link to this item: http://idr.iitbbs.ac.in/jspui/handle/2008/240
Title: A particle-swarm-optimization-based decentralized nonlinear active noise control system
Authors: George N.V.
Panda G.
Keywords: Adaptive filter
decentralized control
functional link artificial neural network (FLANN)
nonlinear active noise control (ANC)
particle swarm optimization (PSO)
Issue Date: 2012
Citation: 49
Abstract: This paper proposes a functional-link-artificial-neural-network-based (FLANN) multichannel nonlinear active noise control (ANC) system trained using a particle swarm optimization (PSO) algorithm suitable for nonlinear noise processes. The use of PSO algorithm in a multichannel ANC environment not only reduces the local minima problem but also removes the requirement of computationally expensive modeling of the secondary-path transfer functions. A decentralized version of a multichannel nonlinear ANC is also developed, which facilitates scaling up of an existing ANC setup without rederiving the learning rules. This is possible as the controller module of each channel is independent of others. Simulation study of the two new multichannel ANC systems demonstrates comparable mitigation performance. However, the decentralized one is preferred to as it possesses the added advantage of scalability. � 1963-2012 IEEE.
URI: http://dx.doi.org/10.1109/TIM.2012.2205492
http://10.10.32.48:8080/jspui/handle/2008/240
Appears in Collections:Research Publications

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