DSpace Repository :: Browsing by Subject "TEORIA DE LA INFORMACION"

Browsing by Subject "TEORIA DE LA INFORMACION"

Now showing 1 - 11 of 11

Analysis of ischaemic crisis using the informational causal entropy-complexity plane
(2018-07) Legnani, Walter; Traversaro Varela, Francisco; Redelico, Francisco; Cymberknop, Leandro J.; Armentano, Ricardo L.; Rosso, Osvaldo A.
"In the present work, an ischaemic process, mainly focused on the reperfusion stage, is studied using the informational causal entropy-complexity plane. Ischaemic wall behavior under this condition was analyzed through wall thickness and ventricular pressure variations, acquired during an obstructive flow maneuver performed on left coronary arteries of surgically instrumented animals. Basically, the induction of ischaemia depends on the temporary occlusion of left circumflex coronary artery (which supplies blood to the posterior left ventricular wall) that lasts for a few seconds. Normal perfusion of the wall was then reestablished while the anterior ventricular wall remained adequately perfused during the entire maneuver. The obtained results showed that system dynamics could be effectively described by entropy-complexity loops, in both abnormally and well perfused walls. These results could contribute to making an objective indicator of the recovery heart tissues after an ischaemic process, in a way to quantify the restoration of myocardial behavior after the supply of oxygen to the ventricular wall was suppressed for a brief period."
Bandt-Pompe symbolization dynamics for time series with tied values: a data-driven approach
(2018-07) Traversaro Varela, Francisco; Redelico, Francisco; Risk, Marcelo; Frery, Alejandro C.; Rosso, Osvaldo A.
"In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from which the permutation entropy can be evaluated. Equalities in the analyzed sequence, for example, repeated equal values, deserve special attention and treatment as was shown recently by Zunino and co-workers [Phys. Lett. A 381, 1883 (2017)]. A significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. In the present contribution, we review the different existing methodologies for treating time series with tied values by classifying them according to their different strategies. In addition, a novel data-driven imputation is presented that proves to outperform the existing methodologies and avoid the false conclusions pointed by Zunino and co-workers."
Characterization of electric load with information theory quantifiers
(2017-01) Aquino, Andre L. L.; Ramos, Heitor S.; Frery, Alejandro C.; Viana, Leonardo P.; Cavalcante, Tamer S. G.; Rosso, Osvaldo A.
"This paper presents a study of the electric load behavior based on the Causality Complexity–Entropy Plane.We use a public data set, namely REDD, which contains detailed power usage information from several domestic appliances. In our characterization, we use the available power data of the circuit/devices of all houses. The Bandt–Pompe methodology combined with the Causality Complexity–Entropy Plane was used to identify and characterize regimes and behaviors over these data. The results showed that this characterization provides a useful insight into the underlying dynamics that govern the electric load."
Crude oil market and geopolitical events: an analysis based on information-theory-based quantifiers
(2016) Fernández Bariviera, Aurelio; Zunino, Luciano; Rosso, Osvaldo A.
"This paper analyzes the informational efficiency of oil market during the last three decades, and examines changes in informational efficiency with major geopolitical events, such as terrorist attacks, financial crisis and other important events. The series under study is the daily prices of West Texas Intermediate (WTI) in USD/BBL, commonly used as a benchmark in oil pricing. The analysis is performed using information-theory-derived quantifiers, namely permutation entropy and permutation statistical complexity. These metrics allow capturing the hidden structure in the market dynamics, and allow discriminating different degrees of informational efficiency. We find that some geopolitical events impact on the underlying dynamical structure of the market."
Diferencias en las aplicaciones de los mapas de entropía de Shannon-entropía de permutación para acciones de mercados de valores de países desarrollados y países en vía de desarrollo
(2014) Micheloni, Matías; Miranda, Lucía; Redelico, Francisco
"Tomando conceptos de los estudios de Zunino et al, se definió un nuevo análisis de las aplicaciones de la Entropía de Permutación aplicada, en este nuevo enfoque, a acciones de mercados de valores, en lugar de índices. El objetivo de este estudio consistió en validar los tres grupos de países propuestos por Zunino et al en su trabajo en base a las series de tiempos de los índices de mercados de valores, promediando los resultados obtenidos de las acciones analizadas en cada país. Luego, se buscaron las diferencias que existen en estas agrupaciones cuando se separan las acciones según la industria a la que pertenece la empresa, lo que resultó en algunos casos muy similar (Oil&Gas y Retail, por ejemplo) y en algunos se requirió cambiar los parámetros del análisis para interpretar los resultados (Power&Energy y Telco, por ejemplo). Finalmente, se realizó un estudio de correlación entre las Entropías de Shannon y de Permutación para hallar una posible interpretación financiera de éstos parámetros. De todos modos, los coeficientes de correlación no resultaron ser los suficientemente grandes como para afirmar que exista una correlación entre ambas, aunque es necesario destacar que éste último análisis mostró una correlación sensiblemente mayor entre el riesgo y la Entropía de Permutación para los países en vías de desarrollo que para los países desarrollados."
Evaluation of the status of rotary machines by time causal information theory quantifiers
(2017-03) Redelico, Francisco; Traversaro Varela, Francisco; Oyarzábal, Nicolás Andrés; Vilaboa, Iván; Rosso, Osvaldo A.
"In this paper several causal Information Theory quantifiers, i.e. Shannon entropy, statistical complexity and Fisher information using the Bandt and Pompe permutation probability distribution, measure are applied to describe the behavior of a rotating machine. An experiment was conducted where a rotating machine runs balanced and then, after a misalignment, runs unbalanced. All the causal Information Theory quantifiers applied are capable to distinguish between both states and grasp the corresponding transition between them. "
Libor at crossroads: stochastic switching detection using information theory quantifiers
(2016-07) Fernández Bariviera, Aurelio; Guercio, M. Belén; Martinez, Lisana B.; Rosso, Osvaldo A.
"This paper studies the 28 time series of Libor rates, classified in seven maturities and four currencies, during the last 14 years. The analysis was performed using a novel technique in financial economics: the Complexity-Entropy Causality Plane. This planar representation allows the discrimination of different stochastic and chaotic regimes. Using a temporal analysis based on moving windows, this paper unveils an abnormal movement of Libor time series around the period of the 2007 financial crisis. This alteration in the stochastic dynamics of Libor is contemporary of what press called "Libor scandal", i.e. the manipulation of interest rates carried out by several prime banks. We argue that our methodology is suitable as a market watch mechanism, as it makes visible the temporal redution in informational efficiency of the market."
Model selection: using information measures from ordinal symbolic analysis to select model subgrid-scale parameterizations
(2017) Pulido, Manuel; Rosso, Osvaldo A.
"The use of information measures for model selection in geophysical models with subgrid parameterizations is examined. Although the resolved dynamical equations of atmospheric or oceanic global numerical models are well established, the development and evaluation of parameterizations that represent subgrid-scale effects pose a big challenge. For climate studies, the parameters or parameterizations are usually selected according to a root-mean-square error criterion that measures the differences between the model-state evolution and observations along the trajectory. However, inaccurate initial conditions and systematic model errors contaminate root-mean-square error measures. In this work, information theory quantifiers, in particular Shannon entropy, statistical complexity, and Jensen–Shannon divergence, are evaluated as measures of the model dynamics. An ordinal analysis is conducted using the Bandt–Pompe symbolic data reduction in the signals. The proposed ordinal information measures are examined in the two-scale Lorenz-96 system. By comparing the two-scale Lorenz-96 system signals with a one-scale Lorenz-96 system with deterministic and stochastic parameterizations, the study shows that information measures are able to select the correct model and to distinguish the parameterizations, including the degree of stochasticity that results in the closest model dynamics to the two-scale Lorenz-96 system."
Propiedades del estimador de la entropía de permutación y su aplicación en problemas de ingeniería
(2018) Traversaro Varela, Francisco; Redelico, Francisco; Risk, Marcelo
"Las medidas provenientes de la Teoría de la Información evaluadas en una distribución de probabilidades adecuada son una herramienta muy potente para caracterizar la complejidad de un sistema dinámico. En particular se estudia la Entropía Informacional de Shannon evaluada en la Función de Distribución de Bandt y Pompe: la Entropía de Permutación. Esta medida es de cómputo rápido, no requiere pre-procesamiento de la señal, contiene información de la estructura de autocorrelaciones de la serie de tiempo y se basa sobre un supuesto de estacionariedad muy débil. La Entropía de Permutación ha sido ampliamente utilizada en aplicaciones de Ingeniería. Sin embrago, hasta el momento el estudio de las propiedades estadísticas de su estimación ha sido poco desarrollado, relegando su utilización a estudios descriptivos de los sistemas dinámicos bajo estudio. En esta Tesis, en una primera instancia se hace un estudio exhaustivo de la Función de Distribución de Bandt Pompe y las distintas metodologías utilizadas para calcularla. Luego se estudian las medidas de complejidad evaluadas en esta distribución y su comportamiento, y se resuelven problemáticas particulares: la aplicación de la Entropía de Permutación a series de tiempo con valores repetidos y la influencia de la distribución marginal de los datos en la estimación de la misma. Finalmente esta Tesis propone una metodología estadística computacional, el bootstrap paramétrico, para obtener una aproximación de la distribución del estimador de la Entropía de Permutación y de esta manera poder hacer inferencia con esta medida de complejidad. Esto permite la construcción de un test estadístico que puede detectar cambios en la dinámica de un proceso mediante la Entropía de Permutación. Se hace un estudio final acerca de la influencia del ruido observacional en la estimación de la Entropía de Permutación mediante el uso de los tests estadísticos propuestos."
RE-SPaM: Using regular expressions for sequential pattern mining in trajectory databases
(2008) Gómez, Leticia Irene; Vaisman, Alejandro Ariel
"In sequential pattern mining, languages based on regular expressions (RE) were proposed to restrict frequent sequences to the ones that satisfy user-specified constraints. In these languages, REs are applied over items. We propose a much powerful language, based on regular expressions, denoted RE-SPaM, where the basic elements are constraints over the attributes of the items. Expressions in this language may include attributes, functions over attributes, and variables. We present the data model, sketch the syntax and semantics of RE-SPaM, a set of examples, and suggest how RE-SPaM can be used in the mining process."
Time series characterization via horizontal visibility graph and Information theory
(2016) Gonçalves, Bruna Amin; Capri, Laura; Rosso, Osvaldo A.; Ravetti, Martín G.
"Complex networks theory have gained wider applicability since methods for transformation of time series to networks were proposed and successfully tested. In the last few years, horizontal visibility graph has become a popular method due to its simplicity and good results when applied to natural and artificially generated data. In this work, we explore different ways of extracting information from the network constructed from the horizontal visibility graph and evaluated by Information Theory quantifiers. Most works use the degree distribution of the network, however, we found alternative probability distributions, more efficient than the degree distribution in characterizing dynamical systems. In particular, we find that, when using distributions based on distances and amplitude values, significant shorter time series are required. We analyze fractional Brownian motion time series, and a paleoclimatic proxy record of ENSO from the Pallcacocha Lake to study dynamical changes during the Holocene."

Browsing by Subject "TEORIA DE LA INFORMACION"

Results Per Page

Sort Options