Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2020
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
versions View all 2 versions
addClaim

PyMODA v0.1.0

Authors: Boškoski, Pavle; Iatsenko, Dmytro; Lancaster, Gemma; McCormack, Sam; Newman, Julian; Guru Vamsi Policharla; Ticcinelli, Valentina; +2 Authors

PyMODA v0.1.0

Abstract

{"references": ["J Newman, G Lancaster and A Stefanovska, \"Multiscale Oscillatory Dynamics Analysis\", v1.01, User Manual, 2018.", "P Clemson, G Lancaster, A Stefanovska, \"Reconstructing time-dependent dynamics\", Proc IEEE 104, 223\u2013241 (2016).", "P Clemson, A Stefanovska, \"Discerning non-autonomous dynamics\", Phys Rep 542, 297-368 (2014).", "D Iatsenko, P V E McClintock, A Stefanovska, \"Linear and synchrosqueezed time-frequency representations revisited: Overview, standards of use, resolution, reconstruction, concentration, and algorithms\", Dig Sig Proc 42, 1\u201326 (2015).", "G Lancaster, D Iatsenko, A Pidde, V Ticcinelli, A Stefanovska, \"Surrogate data for hypothesis testing of physical systems\", Phys Rep 748, 1\u201360 (2018).", "Bandrivskyy A, Bernjak A, McClintock P V E, Stefanovska A, \"Wavelet phase coherence analysis: Application to skin temperature and blood flow\", Cardiovasc Engin 4, 89\u201393 (2004).", "Sheppard L W, Stefanovska A, McClintock P V E, \"Testing for time-localised coherence in bivariate data\", Phys. Rev. E 85, 046205 (2012).", "D Iatsenko, P V E McClintock, A Stefanovska, \"Nonlinear mode decomposition: A noise-robust, adaptive decomposition method\", Phys Rev E 92, 032916 (2015).", "D Iatsenko, P V E McClintock, A Stefanovska, \"Extraction of instantaneous frequencies from ridges in time-frequency representations of signals\", Sig Process 125, 290\u2013303 (2016).", "J Jam\u0161ek, A Stefanovska, P V E McClintock, \"Wavelet bispectral analysis for the study of interactions among oscillators whose basic frequencies are significantly time variable\", Phys Rev E 76, 046221 (2007).", "J Jam\u0161ek, M Palu\u0161, A Stefanovska, \"Detecting couplings between interacting oscillators with time-varying basic frequencies: Instantaneous wavelet bispectrum and information theoretic approach\", Phys Rev E 81, 036207 (2010).", "J Newman, A Pidde, A Stefanovska, \"Defining the wavelet bispectrum\", submitted (2019).", "V N Smelyanskiy, D G Luchinsky, A Stefanovska, P V E McClintock, \"Inference of a nonlinear stochastic model of the cardiorespiratory interaction\", Phys Rev Lett 94, 098101 (2005).", "T Stankovski, A Duggento, P V E McClintock, A Stefanovska, \"Inference of time-evolving coupled dynamical systems in the presence of noise\", Phys Rev Lett 109, 024101 (2012).", "T Stankovski, A Duggento, P V E McClintock, A Stefanovska, \"A tutorial on time-evolving dynamical Bayesian inference\", Eur Phys J \u2013 Special Topics 223, 2685-2703 (2014).", "T Stankovski, T Pereira, P V E McClintock, A Stefanovska, \"Coupling functions: Universal insights into dynamical interaction mechanisms\", Rev Mod Phys 89, 045001 (2017).", "Special issue of the Philos Trans Royal Soc A (2019) with contributions by Kuramoto and others."]}

PyMODA is a Python implementation of MODA, a numerical toolbox developed by the Nonlinear & Biomedical Physics group at Lancaster University for analysing real-life time-series. Algorithms developed by members of: Nonlinear and Biomedical Physics Group, Physics Department, Lancaster University, UK from 2006 until present. Nonlinear Dynamics and Synergetic Group at the Faculty of Electrical Engineering, University of Ljubljana, Slovenia from 1996 to 2006. Aneta Stefanosvka extends her personal thanks to Aleš Založnik, and to her PhD students.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 11
  • 11
    views
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
Average
Average
Average
11