Variable step‐size non‐negative normalised least‐mean‐square‐type algorithm. Issue 8 (1st October 2015)

• Record Type: Journal Article
• Authors: Jung, Sang Mok; Seo, Ji‐Hye; Park, PooGyeon
• Is Part Of: IET signal processing. Volume 9:Issue 8(2015)
• Page Start: 618
• Page End: 622
• Publication Date: 2015-10-01
• Subjects: least mean squares methods -- adaptive filters -- filtering theory -- iterative methods; variable step‐size nonnegative normalised least‐mean‐square‐type algorithm -- adaptive filtering algorithm -- online estimation -- mean‐square deviation analysis -- MSD analysis -- NLMS‐type algorithm -- cost function -- fixed‐point iteration method -- steady‐state estimation error; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2014.0122
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : This paper proposes a fast and precise adaptive filtering algorithm for online estimation under a non‐negativity constraint. A novel variable step‐size (VSS) non‐negative normalised least‐mean‐square (NLMS)‐type algorithm based on the mean‐square deviation (MSD) analysis with a non‐negativity constraint is derived. The NLMS‐type algorithm under the non‐negativity constraint is derived by using the gradient descent of the given cost function and the fixed‐point iteration method. Furthermore, the VSS derived by minimising the MSD yields improvement of the filter performance in the aspects of the convergence rate and the steady‐state estimation error. Simulation results show that the proposed algorithm outperforms existing algorithms.