Inference performance for a system of two phase oscillators: Winfree model.

<p>(a): Mean and standard deviation of the relative bias of the inferred coupling strength. The cyan and magenta solid lines represent the performance of the proposed method and the naive methods, respectively. (b) and (c): Phase time series obtained from the weak (b) and moderate (c) coupling...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Akari Matsuki (22231882) (author)
مؤلفون آخرون: Hiroshi Kori (131680) (author), Ryota Kobayashi (1427098) (author)
منشور في: 2025
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_version_ 1852016724464893952
author Akari Matsuki (22231882)
author2 Hiroshi Kori (131680)
Ryota Kobayashi (1427098)
author2_role author
author
author_facet Akari Matsuki (22231882)
Hiroshi Kori (131680)
Ryota Kobayashi (1427098)
author_role author
dc.creator.none.fl_str_mv Akari Matsuki (22231882)
Hiroshi Kori (131680)
Ryota Kobayashi (1427098)
dc.date.none.fl_str_mv 2025-09-11T17:23:58Z
dc.identifier.none.fl_str_mv 10.1371/journal.pcsy.0000063.g003
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/Inference_performance_for_a_system_of_two_phase_oscillators_Winfree_model_/30105334
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biochemistry
Neuroscience
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
xlink "> synchronization
synchronization strongly depends
may seem counterintuitive
phase reduction theory
control synchronization dynamics
weakly coupled oscillators
proposed method discards
network inference applicable
coupled oscillators
proposed method
established theory
desynchronized oscillators
cycle oscillators
world systems
wider class
time series
simulated data
remains challenging
previous studies
oscillatory systems
observed data
network plays
network inference
method expands
mathematically described
large part
interaction network
desynchronous systems
data used
crucial role
asynchronous systems
dc.title.none.fl_str_mv Inference performance for a system of two phase oscillators: Winfree model.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <p>(a): Mean and standard deviation of the relative bias of the inferred coupling strength. The cyan and magenta solid lines represent the performance of the proposed method and the naive methods, respectively. (b) and (c): Phase time series obtained from the weak (b) and moderate (c) coupling strengths. Note that the natural frequency component is substracted from the phase . Black and gray lines represent the phase of the Winfree model (<a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e095" target="_blank">Eqs 11</a> and <a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e096" target="_blank">12</a>) and its avegared model (<a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e056" target="_blank">Eqs 7</a> and <a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e057" target="_blank">8</a>), respectively. Model parameters are set as , and the coupling strength <i>c</i> = 0.02 (b) and 0.15 (c).</p>
eu_rights_str_mv openAccess
id Manara_35dbe9dadefcfaeff2e8bd5f7a617818
identifier_str_mv 10.1371/journal.pcsy.0000063.g003
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/30105334
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
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rights_invalid_str_mv CC BY 4.0
spelling Inference performance for a system of two phase oscillators: Winfree model.Akari Matsuki (22231882)Hiroshi Kori (131680)Ryota Kobayashi (1427098)BiochemistryNeuroscienceBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedxlink "> synchronizationsynchronization strongly dependsmay seem counterintuitivephase reduction theorycontrol synchronization dynamicsweakly coupled oscillatorsproposed method discardsnetwork inference applicablecoupled oscillatorsproposed methodestablished theorydesynchronized oscillatorscycle oscillatorsworld systemswider classtime seriessimulated dataremains challengingprevious studiesoscillatory systemsobserved datanetwork playsnetwork inferencemethod expandsmathematically describedlarge partinteraction networkdesynchronous systemsdata usedcrucial roleasynchronous systems<p>(a): Mean and standard deviation of the relative bias of the inferred coupling strength. The cyan and magenta solid lines represent the performance of the proposed method and the naive methods, respectively. (b) and (c): Phase time series obtained from the weak (b) and moderate (c) coupling strengths. Note that the natural frequency component is substracted from the phase . Black and gray lines represent the phase of the Winfree model (<a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e095" target="_blank">Eqs 11</a> and <a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e096" target="_blank">12</a>) and its avegared model (<a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e056" target="_blank">Eqs 7</a> and <a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journal.pcsy.0000063#pcsy.0000063.e057" target="_blank">8</a>), respectively. Model parameters are set as , and the coupling strength <i>c</i> = 0.02 (b) and 0.15 (c).</p>2025-09-11T17:23:58ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pcsy.0000063.g003https://figshare.com/articles/figure/Inference_performance_for_a_system_of_two_phase_oscillators_Winfree_model_/30105334CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/301053342025-09-11T17:23:58Z
spellingShingle Inference performance for a system of two phase oscillators: Winfree model.
Akari Matsuki (22231882)
Biochemistry
Neuroscience
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
xlink "> synchronization
synchronization strongly depends
may seem counterintuitive
phase reduction theory
control synchronization dynamics
weakly coupled oscillators
proposed method discards
network inference applicable
coupled oscillators
proposed method
established theory
desynchronized oscillators
cycle oscillators
world systems
wider class
time series
simulated data
remains challenging
previous studies
oscillatory systems
observed data
network plays
network inference
method expands
mathematically described
large part
interaction network
desynchronous systems
data used
crucial role
asynchronous systems
status_str publishedVersion
title Inference performance for a system of two phase oscillators: Winfree model.
title_full Inference performance for a system of two phase oscillators: Winfree model.
title_fullStr Inference performance for a system of two phase oscillators: Winfree model.
title_full_unstemmed Inference performance for a system of two phase oscillators: Winfree model.
title_short Inference performance for a system of two phase oscillators: Winfree model.
title_sort Inference performance for a system of two phase oscillators: Winfree model.
topic Biochemistry
Neuroscience
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
xlink "> synchronization
synchronization strongly depends
may seem counterintuitive
phase reduction theory
control synchronization dynamics
weakly coupled oscillators
proposed method discards
network inference applicable
coupled oscillators
proposed method
established theory
desynchronized oscillators
cycle oscillators
world systems
wider class
time series
simulated data
remains challenging
previous studies
oscillatory systems
observed data
network plays
network inference
method expands
mathematically described
large part
interaction network
desynchronous systems
data used
crucial role
asynchronous systems