Block filtered-s least mean square algorithm for active control of non-linear noise systems

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Block filtered-s least mean square algorithm for active control of non-linear noise systems

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In this study, the authors propose a block formulation of an algorithm, called the block-filtered-s LMS (BFSLMS) algorithm, for active control of non-linear noise processes for a multichannel setup. A reduced structure of the fast Fourier transform (FFT)-based BFSLMS-M (FBFSLMS-M) algorithm has also been studied. From this, the multichannel block filtered-x LMS (FBFXLMS-M) algorithm has been derived as a special case. The simulation results show that these algorithms have a matching performance with the already existing algorithms, with a relatively low computational complexity. A reduced structure delayless FBFSLMS algorithm for the multichannel case has also been developed which has a lesser computational complexity than its time-domain counterpart. Apart from this, it has no delay which, in general, is inherent in the block adaptive algorithms.

Inspec keywords: least mean squares methods; computational complexity; fast Fourier transforms; nonlinear control systems; active noise control

Other keywords: block filtered-s least mean square algorithm; active noise control; computational complexity; fast Fourier transform; block adaptive algorithms; reduced structure delayless FBFSLMS algorithm; multichannel setup; nonlinear noise systems

Subjects: Interpolation and function approximation (numerical analysis); Integral transforms in numerical analysis; Interpolation and function approximation (numerical analysis); Integral transforms in numerical analysis; Other nonelectric variables control; Nonlinear control systems; Signal processing theory; Signal processing and detection

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