DocumentCode :
1475542
Title :
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
Link To Document :
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