UPC’s institutional transformation towards sustainability

Peer ReviewedPostprint (published version

BRAIN COMPUTER INTERFACE - Application of an Adaptive Bi-stage Classifier based on RBF-HMM

Brain Computer Interface is an emerging technology that allows new output paths to communicate the users intentions without the use of normal output paths, such as muscles or nerves. In order to obtain their objective, BCI devices make use of classifiers which translate inputs from the users brain signals into commands for external devices. This paper describes an adaptive bi-stage classifier. The first stage is based on Radial Basis Function neural networks, which provides sequences of pre-assignations to the second stage, that it is based on three different Hidden Markov Models, each one trained with pre-assignation sequences from the cognitive activities between classifying. The segment of EEG signal is assigned to the HMMwith the highest probability of generating the pre-assignation sequence. The algorithm is tested with real samples of electroencephalografic signal, from five healthy volunteers using the cross-validation method. The results allow to conclude that it is possible to implement this algorithm in an on-line BCI device. The results also shown the huge dependency of the percentage of the correct classification from the user and the setup parameters of the classifier

Sharp weighted estimates for classical operators

We give a new proof of the sharp one weight $L^p$ inequality for any operator $T$ that can be approximated by Haar shift operators such as the Hilbert transform, any Riesz transform, the Beurling-Ahlfors operator. Our proof avoids the Bellman function technique and two weight norm inequalities. We use instead a recent result due to A. Lerner to estimate the oscillation of dyadic operators. Our method is flexible enough to prove the corresponding sharp one-weight norm inequalities for some operators of harmonic analysis: the maximal singular integrals associated to $T$, Dyadic square functions and paraproducts, and the vector-valued maximal operator of C. Fefferman-Stein. Also we can derive a very sharp two-weight bump type condition for $T$.Comment: We improve different parts of the first version, in particular we show the sharpness of our theorem for the vector-valued maximal functio

Tree-structure Expectation Propagation for Decoding LDPC codes over Binary Erasure Channels

Expectation Propagation is a generalization to Belief Propagation (BP) in two ways. First, it can be used with any exponential family distribution over the cliques in the graph. Second, it can impose additional constraints on the marginal distributions. We use this second property to impose pair-wise marginal distribution constraints in some check nodes of the LDPC Tanner graph. These additional constraints allow decoding the received codeword when the BP decoder gets stuck. In this paper, we first present the new decoding algorithm, whose complexity is identical to the BP decoder, and we then prove that it is able to decode codewords with a larger fraction of erasures, as the block size tends to infinity. The proposed algorithm can be also understood as a simplification of the Maxwell decoder, but without its computational complexity. We also illustrate that the new algorithm outperforms the BP decoder for finite block-siz

Revueltas : un apocalíptico no integrado

1 archivo PDF (7 páginas). tyvlxliiiEl autor describe su acercamiento a la obra de José Revueltas, en particular dos de ellas: “Dios en la tierra” y “El apando” las cuales describen a mexicanos que contienen en sí a la humanidad entera, enajenada, víctima de su propio no ser, alienados y sin esperanza, propensos a la autodestrucción y negados, como los perros a los que Revueltas increpó en deefeño Parque Hundido

Centro de Ciencia y Tecnología del Parque Tecnológico de Andalucía

Para quienes sienten curiosidad por saber qué es un Parque Tecnológico, cómo funciona, quiénes están y qué hacen. Para los profesores que quieren mostrar a sus alumnos cómo la innovación y el conocimiento generan desarrollo económico y social en nuestra tierr

Superfluid fraction in disordered bosonic gases

Màster Oficial de Ciència i Tecnologia Quàntiques / Quantum Science and Technology, Facultat de Física, Universitat de Barcelona. Curs: 2022-2023. Tutors: Pietro Massignan, Grigori AstrakharchikIn this work, we study the behaviour of the superfluid fraction f of a bosonic system under the influence of a speckle potential. We start by introducing and defining f, and then we present the lower and upper bounds to f derived by A. Leggett for generic many-body systems. To benchmark our codes, we study first the case of a periodic optical potential, reproducing results that recently appeared in the literature. We continue by describing the particular kind of disordered potential we want to study, and how this is characterized. Finally, we compute the superfluid fraction as a function of the intensity of the disordered potential and the interaction strength between the bosons, and we compare our results to the two bounds in both 1D and 2D