The Application of Blind Source Separation to Feature Decorrelation and Normalizations

We apply a Blind Source Separation BSS algorithm to the decorrelation of Mel-warped cepstra. The observed cepstra are modeled as a convolutive mixture of independent source cepstra. The algorithm aims to minimize a cross-spectral correlation at different lags to reconstruct the source cepstra. Results show that using "independent" cepstra as features leads to a reduction in the WER.Finally, we present three different enhancements to the BSS algorithm. We also present some results of these deviations of the original algorithm

Alternatives to free molecular halogens as chemoselective reactants: Catalysis of organic reactions with reusable complexes of halogen metal salts

Organometallic complexes of halogen metallic salts have been used as catalysts in different organic reactions, mainly the oxidation of organic compounds. Their use has not only allowed the reduction of the amounts of catalyst (since they can be reused) but also a lower generation of by-products and wastes. The different reaction media developed through the research were analyzed by several green parameters and the best results were obtained with complexes that have cyclodextrins as organic ligands. The proposed methodology is an alternative to use of molecular halogen as oxidant or catalyst when halogens are significant chemoselective reactants.Fil: Rossi, Laura Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Velasco, Manuel Isaac. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentin

Selection of the Informative Base in ARMA-GARCH Models

In this paper we consider the selection of the information set in ARMA-GARCH models using the methodology proposed in Muñoz et al. (2001) based on ideas of Phillips (1996). To that end, we analyse the performance of some selection criteria asymptotically equivalent to the Bayes factor and propose a method to build approximated Bayesian forecast intervals.ARMA, GARCH, Prediction , Model Selection, Information Set Selection