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Generalized matched subspace filter for dependent noise based on ICA

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IEEE Transactions on Signal Processing

Abstract

We propose a generalization of the matched subspace filter for the detection of unknown signals in a background of non-Gaussian and nonindependent noise. The generalization is based on a modification of the Rao test by including a linear transformation derived from independent component analysis (ICA). Receiver operating characteristic (ROC) curves computed for simulated examples illustrate the significant improvement achieved with the generalized solution. © 2011 IEEE.