Zobrazeno 1 - 10
of 48
pro vyhledávání: '"George, Sandip V."'
Data-driven modelling and scientific machine learning have been responsible for significant advances in determining suitable models to describe data. Within dynamical systems, neural ordinary differential equations (ODEs), where the system equations
Externí odkaz:
http://arxiv.org/abs/2404.18572
The reasons behind the Great Dimming and subsequent rising in the brightness of Betelgeuse between October 2019 and March 2020 still continue to baffle astronomers. It has been shown by George et. al. (2020) that critical slowing down preceded the di
Externí odkaz:
http://arxiv.org/abs/2111.09218
In this topical review, we present a brief overview of the different methods and measures to detect the occurrence of critical transitions in complex systems. We start by introducing the mechanisms that trigger critical transitions, and how they rela
Externí odkaz:
http://arxiv.org/abs/2107.01210
Publikováno v:
A&A 640, L21 (2020)
Critical transitions occur in complex dynamical systems, when the system dynamics undergoes a regime shift. These can often occur with little change in the mean amplitude of system response prior to the actual time of transition. The recent dimming a
Externí odkaz:
http://arxiv.org/abs/2006.16086
Close binary stars are binary stars where the component stars are close enough such that they can exchange mass and/or energy. They are subdivided into semi-detached, overcontact or ellipsoidal binary stars. A challenging problem in the context of cl
Externí odkaz:
http://arxiv.org/abs/1907.10602
Overcontact binary stars are systems of two stars where the component stars are in contact with each other. This implies that they share a common envelope of gas. In this work we seek signatures of nonlinearity and chaos in these stars by using time
Externí odkaz:
http://arxiv.org/abs/1805.08351
Autor:
George, Sandip V., Ambika, G.
Publikováno v:
Indian Academy of Sciences Conference Series (2017) 1:1
Datagaps are ubiquitous in real world observational data. Quantifying nonlinearity in data having gaps can be challenging. Reported research points out that interpolation can affect nonlinear quantifiers adversely, artificially introducing signatures
Externí odkaz:
http://arxiv.org/abs/1705.00416
Publikováno v:
Nonlinear Dyn (2017) 89: 465
Deriving meaningful information from observational data is often restricted by many limiting factors, the most important of which is the presence of noise. In this work, we present the use of the bicoherence function to extract information about the
Externí odkaz:
http://arxiv.org/abs/1608.05206
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Astrophys Space Sci (2015) 360:5
Observational data, especially astrophysical data, is often limited by gaps in data that arises due to lack of observations for a variety of reasons. Such inadvertent gaps are usually smoothed over using interpolation techniques. However the smoothin
Externí odkaz:
http://arxiv.org/abs/1410.4454