The present contribution aims at extending the classical scalar ARMA (auto-regressive moving-average) model to generate random (as well as deterministic) paths on complex-valued matrix Lie groups. The numerical properties of the developed ARMA model are studied by recurring to a tailored version of the Z-transform on Lie groups and to statistical indicators tailored to Lie groups, such as correlation functions on tangent bundles. The numerical behavior of the devised ARMA model is also illustrated by numerical simulations.
Auto-Regressive Moving Average Models on Complex-Valued Matrix Lie Groups / Fiori, Simone. - In: CIRCUITS SYSTEMS AND SIGNAL PROCESSING. - ISSN 0278-081X. - STAMPA. - 33:8(2014), pp. 2449-2473. [10.1007/s00034-014-9745-1]
Auto-Regressive Moving Average Models on Complex-Valued Matrix Lie Groups
FIORI, Simone
2014-01-01
Abstract
The present contribution aims at extending the classical scalar ARMA (auto-regressive moving-average) model to generate random (as well as deterministic) paths on complex-valued matrix Lie groups. The numerical properties of the developed ARMA model are studied by recurring to a tailored version of the Z-transform on Lie groups and to statistical indicators tailored to Lie groups, such as correlation functions on tangent bundles. The numerical behavior of the devised ARMA model is also illustrated by numerical simulations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
