# Study of filtered-x logarithmic recursive least p-power algorithm

arXiv: https://arxiv.org/abs/2202.00560 · HTML: https://mlsanity.com/paper/2202.00560/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 93 references that are in the map.
- First posted on arXiv 20 Jan 2022.

## Builds on (most cited first, 4 of 4)

- [Design of Robust Adaptive Beamforming Algorithms Based on Low-Rank and Cross-Correlation Techniques](https://mlsanity.com/paper/1606.01313/) (2016)
- [Direction Finding Algorithms with Joint Iterative Subspace Optimization](https://mlsanity.com/paper/1402.2710/) (2014)
- [Sparsity-Aware Adaptive Algorithms Based on Alternating Optimization with Shrinkage](https://mlsanity.com/paper/1401.0463/) (2014)
- [Subspace-Orbit Randomized Decomposition for Low-rank Matrix Approximation](https://mlsanity.com/paper/1804.00462/) (2018)

## Abstract (arXiv)

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 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.