Un método para alinear series temporales basado en características de la envolvente como punto de anclaje

In the field of time series analysis, there is not a unique recipe for studying signal similarities. When having the repetition of a pattern, averaging different signals of the same nature could be complicated. Sometimes averaging is essential in the analysis of the data. Here we propose a method to align and average segments of time series with similar patterns. For this procedure, a simple implementation based on python code is provided. This analysis was inspired by the study of canary sound syllables, but it is possible to apply it in semi-periodic signals of different nature, not necessarily related to sounds.Fil: Jarne, Cecilia Gisele. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentin

A method for estimation of fundamental frequency for tonal sounds inspired on bird song studies

In this work a simple implementation of fundamental frequency estimation is presented. The algorithm is based on a frequency-domain approach. It was mainly developed for tonal sounds and it was used in Canary birdsong analysis. The method was implemented but not restricted for this kind of data. It could be easily adapted for other sounds. Python libraries were used to develop a code with a simple algorithm to obtain fundamental frequency. An open source code is provided in the local university repository and Github. • The algorithm and the implementation are very simple and cover a set of potential applications for signal analysis.• Code implementation is written in python, very easy to use and modify.• Present method is proposed to analyze data from sounds of Serinus canaria.Fil: Jarne, Cecilia Gisele. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Effect in the spectra of eigenvalues and dynamics of RNNs trained with Excitatory-Inhibitory constraint

In order to comprehend and enhance models that describes various brain regions is important to study the dynamics of trained recurrent neural networks. Including Dales law in such models usually presents several challenges. However, this is an important aspect that allows computational models to better capture the characteristics of the brain. Here we present a framework to train networks using such constraint. Then we have used it to train them in simple decision making tasks. We characterized the eigenvalue distributions of the recurrent weight matrices of such networks. Interestingly, we discovered that the non-dominant eigenvalues of the recurrent weight matrix are distributed in a circle with a radius less than 1 for those whose initial condition before training was random normal and in a ring for those whose initial condition was random orthogonal. In both cases, the radius does not depend on the fraction of excitatory and inhibitory units nor the size of the network. Diminution of the radius, compared to networks trained without the constraint, has implications on the activity and dynamics that we discussed here

Recurrent Neural Networks as Electrical Networks, a formalization

Since the 1980s, and particularly with the Hopfield model, recurrent neural networks or RNN became a topic of great interest. The first works of neural networks consisted of simple systems of a few neurons that were commonly simulated through analogue electronic circuits. The passage from the equations to the circuits was carried out directly without justification and subsequent formalisation. The present work shows a way to formally obtain the equivalence between an analogue circuit and a neural network and formalizes the connection between both systems. We also show which are the properties that these electrical networks must satisfy. We can have confidence that the representation in terms of circuits is mathematically equivalent to the equations that represent the network

Composition studies of Ultra High Energy Cosmic Rays at the Pierre Auger Observatory

To understand the origin and nature of Ultra High Energy Cosmic Rays their mass composition must be known. The Pierre Auger Observatory is an instrument which provides valuable information for the determination of the primary mass. Different parameters that describe various characteristics of the shower development and at the same time are sensitive to the primary mass are discussed. Their energy dependence and a comparison with predictions from different models are also presented.Facultad de Ciencias Exacta

Composition studies of Ultra High Energy Cosmic Rays at the Pierre Auger Observatory

To understand the origin and nature of Ultra High Energy Cosmic Rays their mass composition must be known. The Pierre Auger Observatory is an instrument which provides valuable information for the determination of the primary mass. Different parameters that describe various characteristics of the shower development and at the same time are sensitive to the primary mass are discussed. Their energy dependence and a comparison with predictions from different models are also presented.Facultad de Ciencias Exacta

Estudios de composición primaria en base a distribuciones temporales en el detector de superficie del Observatorio Pierre Auger

El presente trabajo de tesis se enmarca dentro de las actividades de investigación del Observatorio Pierre Auger. En particular, se estudió la posibilidad de utilizar un nuevo parámetro sensible a composición, que surge del estudio de las distribuciones de tiempos de arribo de las partículas secundarias en los detectores de superficie. La idea general consiste en utilizar el valor del risetime de las señales en los detectores de superficie a 1000 metros del punto de impacto de la lluvia (R1000), estudiando la forma de las distribuciones obtenidas a partir de dicho parámetro. En el proceso de construcción del nuevo parámetro que describe la forma de las distribuciones de R1000, se ha contribuido también a la optimización del cálculo del risetime y sus incertezas. En el capítulo 1 del presente trabajo se introduce el marco teórico relacionado a los rayos cósmicos ultraenergéticos. Se presentar a la física relacionada con las cascadas de partículas secundarias destacando las propiedades sensibles a composición primaria. En los capítulos 2 y 3 se describe el Observatorio Pierre Auger y el modo en que son detectadas las lluvias de partículas, dando una explicación detallada del funcionamiento del detector. En el capítulo 4 se mostrarán los resultados más relevantes obtenidos por la colaboración del Observatorio Pierre Auger. A partir del capítulo 5 se describen los estudios específicos y originales realizados en el marco del presente trabajo de tesis. En el capítulo 5 se presentan los resultados de estudios de estabilidad a largo plazo del detector de superficie, fundamentales para todo análisis basado en los datos de dicho detector. En el capítulo 6, se presentan los resultados obtenidos para la optimización en el cálculo del risetime a 1000 metros así como las modificaciones que a partir de estos estudios se han incluido en el software de reconstrucción de las lluvias. El capítulo 7 contiene los estudios realizados sobre la distribución del risetime a 1000 metros y los parámetros que describen su forma, analizando su evolución en función de la energía. Se discuten también los resultados obtenidos. Finalmente en el capítulo 8 se presentan los resultados del análisis estadístico efectuado sobre las distribuciones completas de R1000, y su discusión. Finalmente se presentan las conclusiones y perspectivas futuras a partir de esta tesis.Facultad de Ciencias Exacta

Markov-chain approach to the distribution of ancestors in species of biparental reproduction

We studied how to obtain a distribution for the number of ancestors in species of sexual reproduction. Present models concentrate on the estimation of distributions repetitions of ancestors in genealogical trees. It has been shown that it is not possible to reconstruct the genealogical history of each species along all its generations by means of a geometric progression. This analysis demonstrates that it is possible to rebuild the tree of progenitors by modeling the problem with a Markov chain. For each generation, the maximum number of possible ancestors is different. This presents huge problems for the resolution. We found a solution through a dilation of the sample space, although the distribution defined there takes smaller values with respect to the initial problem. In order to correct the distribution for each generation, we introduced the invariance under a gauge (local) group of dilations. These ideas can be used to study the interaction of several processes and provide a new approach on the problem of the common ancestor. In the same direction, this model also provides some elements that can be used to improve models of animal reproduction.Instituto de Física La Plat