Information and Knowledge Valuation using the Information Theory and Informative Matrices

For a more concrete analysis of the quantification of knowledge, one must normalize the quantification of data and information. One must, without entering into excessive detail, resort to the information theory, recognizing three features that data, information and knowledge have in common: weight, content and quantity. The following article is an introduction to and conceptualization, in the light of the Information Theory (IT), of the quantification of information and knowledge by means of informative matrices and a normalization valid for every IT organization. Key words: Data, information, knowledge, informative quantity, informative weight, informative content, informative matrix, information theory, generate

Relative Radiometric Normalization of Multitemporal images

A correct radiometric normalization between both images is fundamental for change detection. MAD method and its IR-MAD extension in an implementation on multisprectral aerial images is described in this paper

Comparative Analysis of Greedy Pursuits for the Order Reduction of Wideband Digital Predistorters

This paper provides a review of greedy pursuits for optimizing Volterra-based behavioral models structure and estimating its parameters. An experimental comparison of the digital predistortion (DPD) linearization performance achieved by these approaches for model-order reduction, such as compressive sampling matching pursuit (CoSaMP), subspace pursuit (SP), orthogonal matching pursuit (OMP), and the novel doubly OMP (DOMP), is presented. A benchmark of the techniques in the DPD of a commercial class AB power amplifier (PA) and a class J PA operating over a 15-MHz Long-Term Evolution (LTE) signal is presented, giving a clear overview of their pruning characteristics in terms of linearization indicators and regressor selection capabilities. In addition, the benchmark is run in a cross-validation scheme by identifying the DPD with a 30-MHz 5G-new radio (NR) signal and validating with the same signal and a 20-MHz multicarrier wideband code division multiple access (WCDMA) signal. The DOMP is shown to be a promising technique since it achieves an enhanced model-order reduction for a similar linearization performance and precision

A bivariate volterra series model for the design of power amplifier digital predistorters

(This article belongs to the Special Issue Energy-Efficient Wireless Communication Systems)The operation of the power amplifier (PA) in wireless transmitters presents a trade-off between linearity and power efficiency, being more efficient when the device exhibits the highest nonlinearity. Its modeling and linearization performance depend on the quality of the underlying Volterra models that are characterized by the presence of relevant terms amongst the enormous amount of regressors that these models generate. The presence of PA mechanisms that generate an internal state variable motivates the adoption of a bivariate Volterra series perspective with the aim of enhancing modeling capabilities through the inclussion of beneficial terms. In this paper, the conventional Volterra-based models are enhanced by the addition of terms, including cross products of the input signal and the new internal variable. The bivariate versions of the general full Volterra (FV) model and one of its pruned versions, referred to as the circuit-knowledge based Volterra (CKV) model, are derived by considering the signal envelope as the internal variable and applying the proposed methodology to the univariate models. A comparative assessment of the bivariate models versus their conventional counterparts is experimentally performed for the modeling of two PAs driven by a 30 MHz 5G New Radio signal: a class AB PA and a class J PA. The results for the digital predistortion of the class AB PA under a direct learning architecture reveal the benefits in linearization performance produced by the bivariate CKV model structure compared to that of the univariate CKV model.Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación TEC2017-82807-PFondo Europeo de Desarrollo Regiona

Presencia de Franklin Pease

No presenta resumen

Utilización del recambio plasmático como herramienta terapéutica en la práctica clínica.

To descrive the use of therapeutic plasma exchange in several pathologies and its adjustment to international reference guides. Observational, descriptive, retrospective study, of all the patients that  received plasmapheresis between January 2014-December 2015. We analized  the appropriate indication according to the bibliography consulted, and the  therapeutic outcome. Indication, replaced volume of plasma, number of sessions  and periodicity were established by the Hematology Service depending  on the disease and its clinical course. 10 patients (8 women), between 28-72 years old, received therapeutic  plasma exchange. The pathologies treated were  eurological (9 patients), Waldenström disease (1 patient). The technique used  was continuous centrifugation with albumin 5% as replacement fluid. The therapeutic plasma exchange in reviewed patients agreed to  reference guides. There was not a direct relation between the recommendation  grade and the response obtained. The reduced number of patients is a limitation  to obtain conclusive results.Objetivo: Describir la utilización del recambio plasmático terapéutico (RPT) en distintas patologías y su ajuste a las guías internacionales de referencia. Método: Estudio observacional, descriptivo y retrospectivo en pacientes que recibieron plasmaféresis entre enero de 2014 y diciembre de 2015. Se analizó la adecuación de su indicación según la bibliografía consultada, así como la respuesta obtenida. El Servicio de Hematología estableció la indicación, el volumen plasmático a recambiar, el número de sesiones y la periodicidad según la enfermedad de base y su evolución clínica. Resultados: Diez pacientes (8 mujeres) entre 28 y 72 años de edad, recibieron RPT. Las patologías eran de origen neurológico (9 pacientes), enfermedad de Waldenström (1 paciente). La técnica utilizada fue centrifugación continua con albúmina 5% como líquido de reposición. Conclusiones: El RPT en los pacientes revisados se ajustó a las guías de referencia. No se observó correlación directa entre el grado de recomendación establecido por dichas guías y la respuesta obtenida. El número reducido de pacientes supone una limitación a la hora de extraer resultados concluyentes

Exploring the Interactions Between Neurophysiology and Cognitive and Behavioral Changes Induced by a Non-pharmacological Treatment: A Network Approach

Dementia due to Alzheimer’s disease (AD) is a neurological syndrome which has an increasing impact on society, provoking behavioral, cognitive, and functional impairments. AD lacks an effective pharmacological intervention; thereby, non-pharmacological treatments (NPTs) play an important role, as they have been proven to ameliorate AD symptoms. Nevertheless, results associated with NPTs are patient-dependent, and new tools are needed to predict their outcome and to improve their effectiveness. In the present study, 19 patients with AD underwent an NPT for 83.1 ± 38.9 days (mean ± standard deviation). The NPT was a personalized intervention with physical, cognitive, and memory stimulation. The magnetoencephalographic activity was recorded at the beginning and at the end of the NPT to evaluate the neurophysiological state of each patient. Additionally, the cognitive (assessed by means of the Mini-Mental State Examination, MMSE) and behavioral (assessed in terms of the Dementia Behavior Disturbance Scale, DBD-13) status were collected before and after the NPT. We analyzed the interactions between cognitive, behavioral, and neurophysiological data by generating diverse association networks, able to intuitively characterize the relationships between variables of a different nature. Our results suggest that the NPT remarkably changed the structure of the association network, reinforcing the interactions between the DBD-13 and the neurophysiological parameters. We also found that the changes in cognition and behavior are related to the changes in spectral-based neurophysiological parameters. Furthermore, our results support the idea that MEG-derived parameters can predict NPT outcome; specifically, a lesser degree of AD neurophysiological alterations (i.e., neural oscillatory slowing, decreased variety of spectral components, and increased neural signal regularity) predicts a better NPT prognosis. This study provides deeper insights into the relationships between neurophysiology and both, cognitive and behavioral status, proving the potential of network-based methodology as a tool to further understand the complex interactions elicited by NPTs

An Upgraded Dual-Band Digital Predistorter Model for Power Amplifiers Linearization

Digital predistortion (DPD) based on Volterra models is commonly employed to counteract the nonlinear distortion of power amplifiers. However, when concurrent dual-band signals are transmitted, 2-D DPD models are required. In this work, upgrading of a standard dual-band model is proposed and justified using multinomial theorem. The linearization performance of the current proposal has been compared to the unextended model. Fifth generation (5G) New Radio signals have been generated to compose a dual-band signal, which later was employed as input signal at Chalmers University of Technology's RF WebLab. Using coefficient selection techniques, the most relevant regressors are shown, and the importance of the new extension is proven. Linearization results highlight the benefits of this proposal.Comisión Europea, Fondo Europeo de Desarrollo RegionalMinisterio de Economía y Competitividad TEC2017-82807-

On the Optimum Number of Coefficients of Sparse Digital Predistorters: A Bayesian Approach

This work presents insights on the application of the Bayesian information criterion (BIC) to fix the optimum number of coefficients in the Volterra series applied to the modeling and linearization of power amplifiers (PAs). The BIC is transformed from a rule to be applied after selection techniques to a stopping criterion, which enables the halting of the algorithm when a condition is reached. This study reveals that the BIC is equivalent to allow a certain identification normalized mean square error (NMSE) decrease after the inclusion of a model component. Experimental results of the digital predistortion of a class J PA are provided, demonstrating the proposal applicability in the attaining of the optimum number of coefficients. A comparison is made between the results obtained when the stopping rule is applied to the hill climbing (HC) and the doubly orthogonal matching pursuit (DOMP) algorithms