Study of filtered-x logarithmic recursive least $p$-power algorithm
This work addresses noise control in specific engineering applications, representing an incremental improvement over prior algorithms.
The paper tackled active impulsive noise control by proposing a filtered-x logarithmic recursive least p-power (FxlogRLP) algorithm, which improved convergence rate and noise reduction compared to existing methods, as demonstrated in simulations.
For active impulsive noise control, a filtered-x recursive least $p$-power (FxRLP) algorithm is proposed by minimizing the weighted summation of the $p$-power of the \emph{a posteriori} errors. Since the characteristic of the target noise is investigated, the FxRLP algorithm achieves good performance and robustness. To obtain a better performance, we develop a filtered-x logarithmic recursive least $p$-power (FxlogRLP) algorithm which integrates the $p$-order moment with the logarithmic-order moment. Simulation results demonstrate that the FxlogRLP algorithm is superior to the existing algorithms in terms of convergence rate and noise reduction.