Distortion Measures for Sparse Signals
Atanas P. Gotchev, Karen Egiazarian · 2005
An important issue in Blind Source Separation (BSS) is how to measure the similarity between a true source and its estimate. This is a simple but not completely trivial topic that has been a bit overlooked in the literature. Special problems arise when the source signals are sparse and the BSS problem is degenerate (i.e. we have more sources than observed mixtures). In this paper we review the most popular distortion measures that have been used to assess the performance of different BSS algorithms. We show that the common distortion measures are not suitable for the degenerate blind separation of sparse sources. Finally we propose a class of alternative distortion measures for sparse sources.