Contribuições ao estudo da dinâmica na teoria da informação: aplicações em clustering dinâmico
Information Theory is a branch of mathematics, more specifically probability theory, that studies information quantification. Recently, several researches have been successful with the use of Information Theoretic Learning (ITL) as a new technique of unsupervised learning. In these works, informa...
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| Formato: | doctoralThesis |
| Idioma: | por |
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Brasil
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/26209 |
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| Resumo: | Information Theory is a branch of mathematics, more specifically probability theory,
that studies information quantification. Recently, several researches have been successful
with the use of Information Theoretic Learning (ITL) as a new technique of unsupervised
learning. In these works, information measures are used as criterion of optimality in
learning. In this work, we will analyze a still unexplored aspect of these information measures,
their dynamic behavior. The main objective of this work is to investigate the use
of measures of information theory in the context of dynamic processes. For this, the same
was done in 3 (three) distinct phases. In the first phase we investigated the presence of
dynamics in the information in the processes. As a source of dynamic information, videos
with different characteristics were used. The second phase presents a new representation
for dynamical processes by state space called Information State Representation. In this
representation, the states of the system are described as a function of the information measures
of the system. To validate this new form of representation, some experiments were
carried out with videos aiming at evaluating its quality when submitted to different dynamic
aspects. In the third phase, we investigated the use of measures based on information
theory within the area of dynamic clustering. The objective in this phase was to compare
the performance of the use of measures of information theory with traditional measurements
in the operations of merge and split between clusters. The results obtained in all
the phases were quite satisfactory meeting the objectives proposed in the work. |
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