The paper derives an optimal step-size for the least-mean-fourth adaptive filter by minimizing mean-square deviation at each iteration, reporting large steady-state gains over NLMF and VSSLMFQ in low-SNR simulations.
Normalised spline adaptive filtering algorithm for nonlinear system identification [J]
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2019 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Optimal step-size of least mean absolute fourth algorithm in low SNR
The paper derives an optimal step-size for the least-mean-fourth adaptive filter by minimizing mean-square deviation at each iteration, reporting large steady-state gains over NLMF and VSSLMFQ in low-SNR simulations.