New Gradient-Based Variable Step Size LMS Algorithms. (13th March 2008)

• Record Type: Journal Article
• Authors: Zhang Zhang, Yonggang Yonggang; Li Li, Ning Ning; Chambers Chambers, Jonathon A. Jonathon A.; Hao Hao, Yanling Yanling
• Other Names: Makino Makino S. S. Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-03-13
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/529480
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : Two new gradient-based variable step size least-mean-square (VSSLMS) algorithms are proposed on the basis of a concise assessment of the weaknesses of previous VSSLMS algorithms in high-measurement noise environments. The first algorithm is designed for applications where the measurement noise signal is statistically stationary and the second for statistically nonstationary noise. Steady-state performance analyses are provided for both algorithms and verified by simulations. The proposed algorithms are also confirmed by simulations to obtain both a fast convergence rate and a small steady-state excess mean square error (EMSE), and to outperform existing VSSLMS algorithms. To facilitate practical application, parameter choice guidelines are provided for the new algorithms.