An LMS adaptive second-order Volterra filter with a zeroth-order term: steady-state performance analysis in a time-varying environment

Author

Sayadi, Mounir ; Fnaiech, Farhat ; Najim, Mohamed

Author_Institution

Ecole Superieure des Sci. et Tech. de Tunis, Tunisia

Volume

47

Issue

3

fYear

1999

fDate

3/1/1999 12:00:00 AM

Firstpage

872

Lastpage

876

Abstract

This article studies the steady-state performance of the least mean square (LMS) adaptive second-order Volterra filter (SOVF) with a zeroth-order term for Gaussian inputs. The mean-square-error (MSE) criterion is evaluated first. Then, SOV LMS algorithm-based updating equations are derived. Next, the steady-state performance of the recursions is analyzed for a random walk model for the unknown system parameters, and the steady-state excess MSE is evaluated. Finally, the theoretical performance predictions are shown to be in good agreement with simulation results, especially for small step sizes

Keywords

adaptive filters; adaptive signal processing; filtering theory; least mean squares methods; nonlinear filters; Gaussian inputs; LMS adaptive second-order Volterra filter; MSE criterion; least mean square; mean-square-error; optimal coefficient; performance predictions; quadratic nonlinear filter; random walk model; simulation results; small step sizes; steady-state excess MSE; steady-state performance analysis; system parameters; time-varying environment; updating equations; zeroth-order term; Adaptive filters; Algorithm design and analysis; Convergence; Degradation; Equations; Least squares approximation; Nonlinear filters; Performance analysis; Predictive models; Steady-state;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.747794

Filename

747794