DocumentCode
1658219
Title
A transient analysis for the convex combination of adaptive filters
Author
Nascimento, Vítor H. ; Silva, Magno T M ; Candido, Renato ; Arenas-García, Jerónimo
Author_Institution
Univ. of Sao Paulo, Sao Paulo, Brazil
fYear
2009
Firstpage
53
Lastpage
56
Abstract
Combination schemes are gaining attention as an interesting way to improve adaptive filter performance. In this paper we pay attention to a particular convex combination scheme with nonlinear adaptation that has recently been shown to be universal -i.e., to perform at least as the best component filter- in steady-state; however, no theoretical model for the transient has been provided yet. By relying on Taylor Series approximations of the nonlinearities, we propose a theoretical model for the transient behavior of such convex combinations. In particular, we provide expressions for the time evolution of the mean and the variance of the mixing parameter, as well as for the mean square overall filter convergence. The accuracy of the model is analyzed for the particular case of a combination of two LMS filters with different step sizes, explaining also how our results can help the designer to adjust the free parameters of the scheme.
Keywords
adaptive filters; approximation theory; least mean squares methods; transient analysis; LMS filters; Taylor series approximations; adaptive filters; mean square overall filter convergence; mixing parameter; nonlinear adaptation; particular convex combination; time evolution; transient analysis; Adaptive filters; Convergence; Error correction; Least squares approximation; Noise reduction; Resonance light scattering; Steady-state; Taylor series; Transient analysis; Transversal filters; Adaptive filters; LMS algorithm; convex combination; transient analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
Conference_Location
Cardiff
Print_ISBN
978-1-4244-2709-3
Electronic_ISBN
978-1-4244-2711-6
Type
conf
DOI
10.1109/SSP.2009.5278642
Filename
5278642
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