High-order contrasts for independent component analysis
Neural Computation
Analysis of astrophysical ice analogs using regularized alternating least squares
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
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Infrared spectroscopy provides direct information on the composition of interstellar dust grains, which play a fundamental role in the evolution of interstellar medium ISM, from cold, quiet and low density molecular clouds to warm, active and dense protostellar ones. The determination of these components is fundamental to predict under the appropriate environmental conditions their evolution, including the appearance of new molecules, radicals and complex organics. The absorption spectrum of the astrophysical ice can be considered the additive linear absorption spectra of the multiple molecules present in the ice, so a linear instantaneous ICA mixture model is appropriate. We present the ICA statement of the problem, discussing the convenience of the model and its advantages in front of supervised methods. We obtain the MAP estimate of the mixing matrix, including its non-negative entries as a prior. We present the results carried out with an ice analogs database, confirming the suitability of the ICA approach.