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Steady-State Mean-Square Performance Analysis of a Relaxed Set-Membership NLMS Algorithm by the Energy Conservation Argument.
- Source :
-
IEEE Transactions on Signal Processing . Sep2009, Vol. 57 Issue 9, p3361-3372. 12p. 2 Black and White Photographs, 1 Chart, 5 Graphs. - Publication Year :
- 2009
-
Abstract
- This paper presents an analysis of the steady-state mean-square error (MSE) of the set-membership normalized least-mean square (SM-NLMS) algorithm with relaxation and regularization parameters. These parameters are introduced for the purpose of deriving in a unified way the steady-state MSE performances of the ϵ-normalized least mean square (ϵ-NLMS) algorithm and a special case of the adaptive parallel subgradient projection (PSP) algorithm. The approach of the paper is to employ the energy conservation relation as a starting point of our analysis. This relation enables us to avoid the transient analysis of the SM-NLMS algorithm, which is in general hard due to the nonlinearity of the SM-NLMS algorithm. As a result, a few nonlinear equations whose solutions are theoretical steady-state MSEs are derived, where two types of reasonable assumptions are introduced to overcome the nonlinearity of the SM-NLMS algorithm. Our results are generalizations of well-known results of the steady-state MSE of the ϵ-NLMS. Extensive simulations show the close agreement between our theories and experiments. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1053587X
- Volume :
- 57
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 44060700
- Full Text :
- https://doi.org/10.1109/TSP.2009.2020747