RT Journal Article
T1 Error covariance matrix estimation of noisy and dynamically coupled time series.
A1 Mera Rivas, María Eugenia
A1 Morán Cabré, Manuel
AB We estimate the covariance matrix of the errors in several dynamically coupled time series corrupted by measurement errors. We say that several scalar time series are dynamically coupled if they record the values of measurements of the state variables of the same smooth dynamical system. The estimation of the covariance matrix of the errors is made using a noise reduction algorithm that efficiently exploits the information contained jointly in the dynamically coupled noisy time series. The method is particularly powerful for short length time series with high uncertainties.
PB Springer Nature
SN 0022-4715
YR 2013
FD 2013
LK https://hdl.handle.net/20.500.14352/42972
UL https://hdl.handle.net/20.500.14352/42972
LA eng
NO Ministerio de Ciencia e Innovación (MICINN)
DS Docta Complutense
RD 2 may 2024