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This paper proposes a novel adaptive bilinear filter-error least mean square (LMS) algorithm and channel-reduced diagonal bilinear filtered-error LMS algorithm, which selectively choose Bilinear channels for coefficient updates in order to reduce computational complexity while still maintaining the performance for nonlinear active noise control. The developed algorithms employ a simple alternative...
In this technical note, the simplified diagonal-structure bilinear filtered-X least mean square (SDBFXLMS) and channel-reduced diagonal-structure bilinear filtered-X least mean square (CRDBFXLMS) algorithms are proposed. Computational complexity for each proposed algorithm is analyzed to show the significant computational reduction in comparison with the diagonal-structure bilinear FXLMS (DBFXLMS)...
This paper proposes an adaptive bilinear filter with a diagonal-channel structure for nonlinear active noise control. Based on the diagonal-channel structure, the diagonal-channel bilinear filtered-X least mean square (DBFXLMS) and recursive least square (DBFXRLS) algorithms are derived. In order to reduce the computational load for the DBFXRLS algorithm, the DBFXRLS algorithm with a sequential channel...
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