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In this paper, the multichannel even mirror Fourier nonlinear (EMFN) filter based filtered-x least mean square (FFLMS) algorithm and filtered-error least mean square (FFELMS) algorithm are proposed for nonlinear active noise control (NANC) applications. The FFLMS algorithm is extended from a single-channel NANC system to a multi-channel NANC system, and the efficient filtered-error structure with...
In this paper, we propose novel adaptive function expansion recursive least square (RLS) algorithms, which can dynamically choose filter channels for coefficient updates for nonlinear active noise control while still maintaining the compromised performance degradation for nonlinear active noise control. The algorithms are developed based on a multi-channel structure using a channel selection scheme...
This paper proposes novel adaptive Volterra recursive least square (RLS) algorithms, which dynamically choose Volterra channels for coefficient updates in order to reduce computational complexity while still maintaining the compromised performance degradation for nonlinear active noise control. The developed algorithms employ a channel selection scheme, which compares an adaptive threshold to the...
In this paper, we propose adaptive second-order Volterra filtered-X recursive least square (RLS) algorithms using sequential and partial updates for nonlinear active noise control. Recent research advancement has demonstrated that nonlinear active control is feasible for applications where the noise to be controlled may be a nonlinear and deterministic noise process such as chaotic noise rather than...
In this paper, we propose a novel two-step antenna selection algorithm for downlink Distributed Multiple Input Multiple Output (D-MIMO) systems. First, the distributed antenna cluster is selected based on maximum path fading, and then the antennas in the selected antenna clusters are chosen utilizing the permutation and QR decomposition (IC-PQRD) method. The analysis and simulation results show that...
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