Source Separation in Chemical Analysis : Recent achievements and perspectives

Since its origins in the mid-1980s, the field of blind source separation (BSS) has attracted considerable attention within the signal processing community. One of the main reasons for such popularity is the existence of many problems that can be addressed in a BSS framework. Two noteworthy examples of applications can be found in audio and biomedical signal processing, for which a number of efficient solutions are now available. There are relevant BSS problems in other domains but on which less effort has been put. In this article, we deal with one of these fields, specifically the field of analytical chemistry (AC), whose goal of is to identify or quantify, or both, chemical components present in a given analyte, i.e., the sample under analysis. As recently discussed in [1], several tasks in AC keep some relationship to the broad classes of detection and estimation problems typically found in signal processing.

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