Cargando…
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...
Autores principales: | Chavez, Mario, Cazelles, Bernard |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6517435/ https://www.ncbi.nlm.nih.gov/pubmed/31089157 http://dx.doi.org/10.1038/s41598-019-43571-2 |
Ejemplares similares
-
Partially coherent imaging and spatial coherence wavelets
por: Castaneda, R
Publicado: (2003) -
Coherent states, wavelets and their generalizations
por: Ali, Syed Twareque, et al.
Publicado: (2000) -
Coherent states, wavelets, and their generalizations
por: Ali, Syed Twareque, et al.
Publicado: (2014) -
Denoising Non-Stationary Signals via Dynamic Multivariate Complex Wavelet Thresholding
por: Raath, Kim C., et al.
Publicado: (2023) -
Robust R-peak detection in an electrocardiogram with stationary wavelet transformation and separable convolution
por: Yun, Donghwan, et al.
Publicado: (2022)