Maiorino, Enrico; Bianchi, Filippo Maria; Livi, Lorenzo; Rizzi, Antonello; Sadeghian, Alireza (Journal article; Tidsskriftartikkel, 2016-12-14)
In this paper, we propose a novel data-driven approach for removing trends (detrending) from
nonstationary, fractal and multifractal time series. We consider real-valued time series relative to
measurements of an underlying dynamical system that evolves through time. We assume that such
a dynamical process is predictable to a certain degree by means of a class of recurrent networks
called Echo ...