A review of blind source separation in NMR spectroscopy
 

A review of blind source separation in NMR spectroscopy


Publication date: August 2014
Source:Progress in Nuclear Magnetic Resonance Spectroscopy, Volume 81</br>
Author(s): Ichrak Toumi , Stefano Caldarelli , Bruno Torrésani</br>
Fourier transform is the data processing naturally associated to most NMR experiments. Notable exceptions are Pulse Field Gradient and relaxation analysis, the structure of which is only partially suitable for FT. With the revamp of NMR of complex mixtures, fueled by analytical challenges such as metabolomics, alternative and more apt mathematical methods for data processing have been sought, with the aim of decomposing the NMR signal into simpler bits. Blind source separation is a very broad definition regrouping several classes of mathematical methods for complex signal decomposition that use no hypothesis on the form of the data. Developed outside NMR, these algorithms have been increasingly tested on spectra of mixtures. In this review, we shall provide an historical overview of the application of blind source separation methodologies to NMR, including methods specifically designed for the specificity of this spectroscopy.
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