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Detecting dynamic spatial correlation patterns with generalized wavelet coherence and non-stationary surrogate data

Time series measured from real-world systems are generally noisy, complex and display statistical properties that evolve continuously over time. Here, we present a method that combines wavelet analysis and non-stationary surrogates to detect short-lived spatial coherent patterns from multivariate ti...

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Библиографические подробности
Опубликовано в: :Sci Rep
Главные авторы: Chavez, Mario, Cazelles, Bernard
Формат: Artigo
Язык:Inglês
Опубликовано: Nature Publishing Group UK 2019
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Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC6517435/
https://ncbi.nlm.nih.gov/pubmed/31089157
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-43571-2
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