Distributed Fusion Estimation with Sensor Gain Degradation and Markovian Delays

This paper investigates the distributed fusion estimation of a signal for a class of multi-sensor systems with random uncertainties both in the sensor outputs and during the transmission connections. The measured outputs are assumed to be affected by multiplicative noises, which degrade the signal, and delays may occur during transmission. These uncertainties are commonly described by means of independent Bernoulli random variables. In the present paper, the model is generalised in two directions: (i) at each sensor, the degradation in the measurements is modelled by sequences of random variables with arbitrary distribution over the interval [0, 1]; (ii) transmission delays are described using three-state homogeneous Markov chains (Markovian delays), thus modelling dependence at different sampling times. Assuming that the measurement noises are correlated and cross-correlated at both simultaneous and consecutive sampling times, and that the evolution of the signal process is unknown, we address the problem of signal estimation in terms of covariances, using the following distributed fusion method. First, the local filtering and fixed-point smoothing algorithms are obtained by an innovation approach. Then, the corresponding distributed fusion estimators are obtained as a matrix-weighted linear combination of the local ones, using the mean squared error as the criterion of optimality. Finally, the efficiency of the algorithms obtained, measured by estimation error covariance matrices, is shown by a numerical simulation example.Ministerio de Economía, Industria y CompetitividadEuropean Union (EU) MTM2017-84199-PAgencia Estatal de Investigació

Estimación lineal en sistemas estocásticos con parámetros distribuidos mediante observaciones inciertas

Univ. Granada, Departamento de Estadística e Investigación Operativa. Leída 23-03-9

The Waring Distribution as a Low-Frequency Prediction Model: A Study of Organic Livestock Farms in Andalusia

Although the numbers are relatively small with respect to non-organic livestock, the importance of organic livestock farms lies in their sustainable coexistence with the natural environment and in the high-quality food products obtained. In this type of production, no artificial chemicals or genetically modified organisms are used, therefore there will be less impact on the environment and, in most cases, native breeds are employed. This paper describes a geostatistical study of organic livestock farms in Andalusia (southern Spain), conducted using information from the 2009 Agricultural Census, by classes of livestock. This region currently records the highest output in Spain for organic livestock farming. The number of farms was fitted according to the univariate generalizedWaring distribution, which is presented as a means of analyzing this type of discrete measurement, using agricultural or livestock data. The Waring distribution is used when the frequency of occurrence of a phenomenon is very low and allows one to divide the variance. The most important outcome of this study is the finding that livestock data variability is mainly due to external factors such as the proneness component of the variance.Faculty of Social and Legal Sciences (Melilla)Department of Statistics and Operational ResearchResearch Group "Survival Analysis and Probability Distributions"Office for Political Science and Research, through the project "Social-Labour Statistics and Demography" at the University of Granada (Spain

MATERIALES INTERACTIVOS PARA LA RESOLUCIÓN DE UN PROBLEMA DE PROGRAMACIÓN LINEAL USANDO EL MÉTODO SIMPLEX

In this paper we present educational interactive materials for a pleasant learning of the resolution of a Linear Programming Problem using the Simplex method. First of them provides, through an example, the steps involved in the graphic resolution of a Linear Programming Problem with two variables. The following materials correspond to the different steps to solve a Linear Programming Problem: Transformation of a Linear Problem to standard form, Construction of the first Simplex table and Simplex Algorithm.En este trabajo presentamos materiales docentes interactivos para un aprendizaje ameno de la resolución de un problema de Programación Lineal mediante el método Simplex. En el primero se proporciona, mediante un ejemplo, los pasos a seguir en la resolución gráfica de un problema de Programación Lineal con dos variables. Los siguientes materiales se corresponden con las distintas fases a seguir desde el planteamiento de un problema de Programación Lineal hasta su resolución: Transformación de un problema de Programación Lineal general a forma estándar, Construcción de la primera tabla del Simplex y Algoritmo Simplex

Nuevas tendencias para enseñar probabilidades usando CDPYE

CDPYE es un entorno interactivo diseñado para proporcionar a los estudiantes de Probabilidad y Estadística un material didáctico atrayente, que complemente los contenidos desarrollados en clase por el profesor, y que les permita poseer un mecanismo de aprendizaje autónomo. Ello se lleva a cabo mediante diversos módulos que incluyen los diferentes pasos que un alumno sigue en el proceso de aprendizaje. En este artículo presentamos el entorno y proporcionamos una descripción de sus módulos, mostrando sus posibilidades, al mismo tiempo que mostramos una experiencia docente llevada a cabo con estudiantes de la Licenciatura en Matemáticas de la Universidad de Granada