M
María Teresa Martín
Researcher at National University of La Plata
Publications - 65
Citations - 3074
María Teresa Martín is an academic researcher from National University of La Plata. The author has contributed to research in topics: Wavelet & Probability distribution. The author has an hindex of 26, co-authored 65 publications receiving 2769 citations. Previous affiliations of María Teresa Martín include National Scientific and Technical Research Council.
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Journal ArticleDOI
Distinguishing noise from chaos.
Osvaldo A. Rosso,Osvaldo A. Rosso,Hilda A. Larrondo,María Teresa Martín,Ángel Luis Plastino,Miguel A. Fuentes,Miguel A. Fuentes +6 more
TL;DR: A representation space is introduced, to be called the complexity-entropy causality plane, which contains suitable functionals of the pertinent probability distribution, namely, the entropy of the system and an appropriate statistical complexity measure, respectively.
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Generalized statistical complexity measures: Geometrical and analytical properties
TL;DR: In this paper, the authors discuss bounds on the values adopted by the generalized statistical complexity measures introduced by Lopez Ruiz et al. and Shiner et al., and prove new theorems with reference to the celebrated logistic map.
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Intensive entropic non-triviality measure
TL;DR: In this article, the Jensen-Shannon divergence is used to measure the complexity of probability distributions, and a measure of complexity called nontriviality is proposed to distinguish different degrees of periodicity.
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EEG analysis using wavelet-based information tools
TL;DR: It is shown that the epileptic recruitment rhythm observed during seizure development is well described in terms of the relative wavelet energies, which is construed as evidence supporting the conjecture that an epileptic focus, for this kind of seizures, triggers a self-organized brain state characterized by both order and maximal complexity.
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Statistical complexity and disequilibrium
TL;DR: In this article, the concept of disequilibrium is used as an essential ingredient of a family of statistical complexity measures, and Wootters' objections to the use of Euclidean distances for probability spaces become quite relevant to this endeavor.