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dc.contributor.author
Restrepo Rinckoar, Juan Felipe
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dc.contributor.author
Schlotthauer, Gaston
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dc.date.available
2020-02-03T17:43:29Z
dc.date.issued
2018-04
dc.identifier.citation
Restrepo Rinckoar, Juan Felipe; Schlotthauer, Gaston; Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice; John Wiley & Sons Inc; Complexity; 2018; 4-2018; 1-9
dc.identifier.issn
1076-2787
dc.identifier.uri
http://hdl.handle.net/11336/96538
dc.description.abstract
Nonlinear measures such as the correlation dimension, the correlation entropy, and the noise level were used in this article to characterize normal and pathological voices. These invariants were estimated through an automated algorithm based on the recently proposed U-correlation integral. Our results show that the voice dynamics have a low dimension. The value of correlation dimension is greater for pathological voices than for normal ones. Furthermore, its value also increases along with the type of the voice. The low correlation entropy values obtained for normal and pathological type 1 and type 2 voices suggest that their dynamics are nearly periodic. Regarding the noise level, in the context of voice signals, it can be interpreted as the power of an additive stochastic perturbation intrinsic to the voice production system. Our estimations suggest that the noise level is greater for pathological voices than for normal ones. Moreover, it increases along with the type of voice, being the highest for type voices. From these results, we can conclude that the voice production dynamical system is more complex in the presence of a pathology. In addition, the presence of the inherent stochastic perturbation strengthens along with the voice type. Finally, based on our results, we propose that the noise level can be used to quantitatively differentiate between type and type voices.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
John Wiley & Sons Inc
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Correlation integral
dc.subject
Correlation entropy
dc.subject
Correlation dimension
dc.subject
Pathological voices
dc.subject.classification
Otras Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
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dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
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dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
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dc.title
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-10-29T18:29:16Z
dc.journal.volume
2018
dc.journal.pagination
1-9
dc.journal.pais
Estados Unidos
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dc.description.fil
Fil: Restrepo Rinckoar, Juan Felipe. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina
dc.journal.title
Complexity
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.hindawi.com/journals/complexity/2018/2173640/
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1155/2018/2173640
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