[Todos CMAT] Excelente noticia

[Jana Rodriguez Hertz]

Excelente noticia, felicitaciones!

El jueves, 9 de julio de 2015, Javier Cóppola <
javier.coppola.rodriguez en gmail.com> escribió:

> Bien los pi!!!!!! Felicitaciones!!!!
> El 09/07/2015 11:56, "Gabriel Núñez" <fnunez en fing.edu.uy
> <javascript:_e(%7B%7D,'cvml','fnunez en fing.edu.uy');>> escribió:
>
>> Que alegría! Felicitaciones Florecía, Pilar y Marcos.
>> El jul 9, 2015 10:23 AM, "Eleonora Catsigeras" <eleonora17 en gmail.com
>> <javascript:_e(%7B%7D,'cvml','eleonora17 en gmail.com');>> escribió:
>>
>>>  Tengo el agrado de compartir con ustedes la siguiente excelente noticia:
>>>
>>> El comité científico del evento EquaDiff 2015
>>> http://equadiff2015.sciencesconf.org/resource/page/id/1
>>> que se está desarrollando en Lyon, Francia
>>> otorgó el primer premio como mejor trabajo presentado en forma póster
>>> al de nuestros compañeros Pilar Lorenzo, Marcos Barrios,  y Florencia
>>> Cubría  (ver título y resumen al pie)
>>>
>>> ¡Felicitaciones a Pilar, Marcos y Florencia!
>>>
>>> Title: Dynamics of cooperative neuronal networks
>>> depending on their associated graphs.
>>> Authors: Pilar Lorenzo (1), Marcos Barrios , and Florencia Cubr ía
>>> Instituto de Matem atica y Estad ística Rafael Laguardia, Universidad de
>>> la Rep ública, Uruguay
>>> (IMERL, UdelaR)
>>>
>>> Abstract
>>> We investigate the dynamics of abstract neuronal networks modelled as
>>> impulsive di fferencial equations on arbitrarily large dimensions, mutually
>>> coupled by impulses. In particular, we study the dynamics that is induced
>>> by the graph of impulsive interactions, for certain classes of graphs.
>>> The methodology of research is mathematical with rigorous proofs based
>>> on the mathematical theory of dynamical systems and the theory of graphs.
>>>
>>> The main tool we use is the consideration of the pulses ocurring in the
>>> whole network during certain time interval. For strongly connected graphs
>>> we prove that every neuron fi res infinitely many times.
>>>
>>> For complete graphs we find an optimal lower bound on the network size
>>> that ensures the existence of the so called "grand coalition". Also, if the
>>> graph is not complete but each neuron has enough connections, the grand
>>> coalition is still present. Finally, we construct extensions from the
>>> strongly connected and star-shaped graphs that also imply the existence
>>> the grand coalition.
>>>
>>> (1) Speaker
>>>
>>>  plorenzo@ fing.edu.uy
>>>  marcosb en fi ng.edu.uy
>>>  fcubria en cmat.edu.uy
>>> <javascript:_e(%7B%7D,'cvml','fcubria en cmat.edu.uy');>
>>>
>>>
>>>
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