On Parallel-Incremental Combinations of LMS Filters that Outperform the Afﬁne Projection Algorithm

Luiz F. O. Chamon; Cássio G. Lopes

doi:10.14209/sbrt.2013.87

On Parallel-Incremental Combinations of LMS Filters that Outperform the Afﬁne Projection Algorithm

Luiz F. O. Chamon, Cássio G. Lopes

DOI: 10.14209/sbrt.2013.87

Evento: XXXI Simpósio Brasileiro de Telecomunicações (SBrT2013)

Keywords: Adaptive ﬁlters Combination of adaptive ﬁlters Parallel-incremental combination Afﬁne Projection Algorithm

Abstract

Data reuse techniques have been successfully applied to improve the performance of adaptive ﬁlters, the Afﬁne Projection Algorithm (APA) being one of the most celebrated examplesofsuchachievements.Recently,incrementalcombinations of LMS ﬁlters have been shown to either match or outperform theAPAwithlowercomplexity.However,thiscombinationbrings forth a trade-off between convergence speed and steady-state error which depends on the number of component ﬁlters. This work proposes a parallel-incremental topology with coefﬁcients feedback to allow transient and steady-state performance to be designed separately. Moreover, to address highly correlated environments, a data reusing incremental combination is employed. An approximate analysis is pursued using the data sharing version of this structure. Numerical experiments show that the novel combination can outperform the convergence rate and misadjustment of the APA and combinations of APAs in different scenarios.

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