Implementing minimum entropy constraint in MCR-ALS
Research output: Contribution to conference › Abstract › Scientific › peer-review
- University of Barcelona
The new constraint is applied by combining the spectral profiles obtained in each iterative cycle of the MCR-ALS algorithm in order to satisfy certain minimum entropy criteria. Several options are explored in the formulation of the combined algorithm: type of optimizer, type of objective function, stop criterion and sequence of application relative to the other constraints. Simulated data sets made by combining real Raman or mass spectra with concentration profiles from a real pharmaceutical image or from a first order reaction were used for this purpose. The best results were obtained in the following conditions: a) using a particle swarm optimizer in the first iteration and a Nelder-Mead simplex for the subsequent ones, b) differentiating the solutions using band targets (i.e. imposing that the solution contains a certain peak) selected by a SIMPLISMA-based method, c) including a non-negativity condition during entropy minimization and d) adding a stop criterion based on similarity among the spectral profiles of consecutive iterations. The sequence of application of the entropy constraint, which was placed either at the very beginning or right after non-negativity, did not have a clear effect on the results.
The proposed algorithm was also assessed on real Raman and IR data. In several cases the inclusion of the entropy constraint brought about a significant improvement as compared to using only non-negativity (see Fig 1), without requiring any additional knowledge on the concentration profiles.
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|Publication status||Published - 2017|
|Event||Scandinavian Symposium on Chemometrics - Naantali Spa, Naantali, Finland|
Duration: 19 Jun 2017 → 22 Jun 2017
Conference number: 15
|Conference||Scandinavian Symposium on Chemometrics|
|Period||19/06/2017 → 22/06/2017|