Robust RLS in the Presence of Correlated Noise Using Outlier Sparsity

Abstract

Relative to batch alternatives, the recursive least-squares (RLS) algorithm has well-appreciated merits of reduced complexity and storage requirements for online processing of stationary signals, and also for tracking slowly-varying nonstationary signals. However, RLS is challenged when in addition to noise, outliers are also present in the data due to, e.g… (More)
DOI: 10.1109/TSP.2012.2189766

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