Stochastic Analysis of a Stable Normalized Least Mean Fourth Algorithm for Adaptive Noise Canceling With a White Gaussian Reference

Autor:	Eweda Eweda, N.J. Bershad
Rok vydání:	2012
Předmět:	Gaussian Filter (signal processing) Stability (probability) Adaptive filter symbols.namesake Noise Additive white Gaussian noise Signal Processing symbols Algorithm design Electrical and Electronic Engineering Gaussian process Algorithm Mathematics
Zdroj:	IEEE Transactions on Signal Processing. 60:6235-6244
ISSN:	1941-0476 1053-587X
DOI:	10.1109/tsp.2012.2215607
Popis:	The least mean fourth (LMF) algorithm has several stability problems. Its stability depends on the variance and distribution type of the adaptive filter input, the noise variance, and the initialization of the filter weights. A global solution to these stability problems was presented recently for a normalized LMF (NLMF) algorithm. Here, a stochastic analysis of the mean-square deviation (MSD) of the globally stable NLMF algorithm is provided. The analysis is done in the context of adaptive noise canceling with a white Gaussian reference input and Gaussian, binary, and uniform desired signals. The analytical model is shown to accurately predict the results of Monte Carlo simulations. Comparisons of the NLMF and NLMS algorithms are then made for various parameter selections. It is then shown under what conditions the NLMF algorithm is superior to NLMS algorithm for adaptive noise canceling.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::fc8d7c85f4c9cea5b13482c5e3741cf9 https://doi.org/10.1109/tsp.2012.2215607 Zobrazit plný text záznamu