Blind Identification, Filtering and Restoration On Spectral Techniques

Project acronym: BIFROST

Topics: data processing, algorithms, multidimensional analyses, spectral techniques

Disciplinary fields: mathematics applied to signal / image, processing analytical chemistry

Summary: This project concerns the development of data processing and data acquisition schemes capable of improving the power of chemical analysis of complex mixtures, in view of achieving a qualitative and quantitative decomposition of instrumental responses, loosely called spectra here after. The challenge resides in producing stable algorithms producing high-purity source representation in the presence of signal distortions and instabilities and, more importantly, a wide dynamic range of molecular concentrations. The most intricate case of study is the one in which the spectrum presents severe overlap, so that more intense signals are likely to obscure the ones from minor species. Thus, an obvious avenue of investigation to improve the detection of less abundant compounds is to seek analytical techniques with increased resolution. A main goal of this project is to develop mathematical and signal processing approaches that stay as close as possible to signal acquisition, e.g. avoiding “black box” preprocessing methods and software. The problem is to integrate such preprocessings in the unmixing problem.

Another goal will be to integrate prior knowledge in the unmixing, e.g. knowledge about spectra of some of the compounds (for example biomarkers or contaminants). 

Project interlocutor: Caroline CHAUX, I2M (UMR 7373)

Project duration: 03/01/2018 – 02/28/2021

Call for application : Interdisciplinarité 2016

Photography credits: Photo by Markus Spiske on Unsplash


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