Colored noise and computational inference in neurophysiological (fMRI) time series analysis: Resampling methods in time and wavelet domains

Dans le contexte que la méthode de Produit Tensoriel espace-temps est encore inexploitée, une étude de la stabilité et de l’estimation de l’erreur de la méthode numérique

We relax the setup from the orthogonal projection to convolution and, using the frequency domain approach, we find a time invariant linear mapping which gives a multivariate series

One of the advantages of using Granger causality is to infer causal networks like gene regulatory networks (GRNs) from microarray time series data [1, 5, 3].. Real biological data

We find that a variation of the DTW kernel: the global alignment (GA) kernel wins when the time series are short in length (<100 temporal dimensions) but when the time series get

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

Although several open questions still have to be addressed before the methodology can be used for the simulation of high–Reynolds number turbulent flows of engineering interest, it

Akaike (1975) has developed a stochastic realization theory based on the information interface between the past and the future of a time series and the concepts of

Moreover, the paper has shown that the statistical properties of geometric wavelets make them good candi- dates for the analysis of SAR image time series: in con- trast with