Learning dynamical regimes of solar active region via homology estimation

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Learning dynamical regimes of solar active region via homology estimation. / Knyazeva, I. S.

2019. 235-242 Paper presented at 7th International Conference on Chaotic Modeling and Simulation, CHAOS 2014, Lisbon, Portugal.

Research output: Contribution to conference › Paper › peer-review

Harvard

Knyazeva, IS 2019, 'Learning dynamical regimes of solar active region via homology estimation', Paper presented at 7th International Conference on Chaotic Modeling and Simulation, CHAOS 2014, Lisbon, Portugal, 7/06/14 - 10/06/14 pp. 235-242.

APA

Knyazeva, I. S. (2019). Learning dynamical regimes of solar active region via homology estimation. 235-242. Paper presented at 7th International Conference on Chaotic Modeling and Simulation, CHAOS 2014, Lisbon, Portugal.

Vancouver

Knyazeva IS. Learning dynamical regimes of solar active region via homology estimation. 2019. Paper presented at 7th International Conference on Chaotic Modeling and Simulation, CHAOS 2014, Lisbon, Portugal.

Author

Knyazeva, I. S. / Learning dynamical regimes of solar active region via homology estimation. Paper presented at 7th International Conference on Chaotic Modeling and Simulation, CHAOS 2014, Lisbon, Portugal.8 p.

BibTeX

@conference{c72c59e97e8e40eebcf04748592cd2f7,

title = "Learning dynamical regimes of solar active region via homology estimation",

abstract = "The development of numerical methods of mathematical morphology and topology gives us opportunity to analyze various structures on the plane and in space. In particular they can be used to analyze the complexity of the image by estimating the variation of the number of connected structures and holes depending on the brightness level. Alternate sum of this numbers gives topological invariant Euler characteristic. The other approach to estimation this characteristic is persistent homology calculation at the different sub level sets. It turned out that the application of these ideas to the active regions of the Sun magnetograms allowed diagnostic changes in different dynamic regimes connected with sun flares.",

keywords = "Dynamical regimes detections, Homology, Mathematical morphology, Sun Active Region, Topological persistence",

author = "Knyazeva, {I. S.}",

note = "Publisher Copyright: {\textcopyright} 2014 ISAST Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 7th International Conference on Chaotic Modeling and Simulation, CHAOS 2014 ; Conference date: 07-06-2014 Through 10-06-2014",

year = "2019",

language = "English",

pages = "235--242",

}

RIS

TY - CONF

T1 - Learning dynamical regimes of solar active region via homology estimation

AU - Knyazeva, I. S.

PY - 2019

Y1 - 2019

N2 - The development of numerical methods of mathematical morphology and topology gives us opportunity to analyze various structures on the plane and in space. In particular they can be used to analyze the complexity of the image by estimating the variation of the number of connected structures and holes depending on the brightness level. Alternate sum of this numbers gives topological invariant Euler characteristic. The other approach to estimation this characteristic is persistent homology calculation at the different sub level sets. It turned out that the application of these ideas to the active regions of the Sun magnetograms allowed diagnostic changes in different dynamic regimes connected with sun flares.

AB - The development of numerical methods of mathematical morphology and topology gives us opportunity to analyze various structures on the plane and in space. In particular they can be used to analyze the complexity of the image by estimating the variation of the number of connected structures and holes depending on the brightness level. Alternate sum of this numbers gives topological invariant Euler characteristic. The other approach to estimation this characteristic is persistent homology calculation at the different sub level sets. It turned out that the application of these ideas to the active regions of the Sun magnetograms allowed diagnostic changes in different dynamic regimes connected with sun flares.

KW - Dynamical regimes detections

KW - Homology

KW - Mathematical morphology

KW - Sun Active Region

KW - Topological persistence

UR - http://www.scopus.com/inward/record.url?scp=85072335157&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85072335157

SP - 235

EP - 242

T2 - 7th International Conference on Chaotic Modeling and Simulation, CHAOS 2014

Y2 - 7 June 2014 through 10 June 2014

ER -

ID: 71884858