Steady-state mean-square performance analysis of a relaxed set-membership NLMS algorithm by the energy conservation argument

Authors:
Noriyuki Takahashi;Isao Yamada
Affiliations:
Department of Communications and Integrated Systems, Tokyo Institute of Technology, Tokyo, Japan;Department of Communications and Integrated Systems, Tokyo Institute of Technology, Tokyo, Japan
Venue:
IEEE Transactions on Signal Processing
Year:
2009

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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.