Title :
Fast stable normalised least-mean fourth algorithm
Author :
Sheng Zhang ; Jiashu Zhang
Author_Institution :
Sichuan Key Lab. of Signal & Inf. Process., Southwest Jiaotong Univ., Chengdu, China
Abstract :
A fast stable normalised least-mean fourth (FSNLMF) algorithm is proposed. The major drawback of the stable normalised least-mean fourth (SNLMF) algorithm is its poor convergence rate, especially in the presence of high signal-to-noise ratios (SNRs). Considering the effect of high SNRs, a corresponding constant is introduced in SNLMF algorithm to offer a fast convergence. Simulations on system identifications demonstrate that the proposed FSNLMF algorithm achieves a faster convergence speed than the SNLMF algorithm.
Keywords :
least mean squares methods; signal processing; FSNLMF algorithm; SNR; fast stable normalised least-mean fourth algorithm; signal-to-noise ratio;
Journal_Title :
Electronics Letters
DOI :
10.1049/el.2015.0421