In many practical situations the process data are affected by noise on both inputs and outputs. In these contexts, errors–in–variables (EIV) models can be the best choice for identification purposes and several approaches based on these representation are present in the literature. This work refers to one of these methods, the so–called dynamic Frisch scheme. In particular, two different Frisch scheme–based algorithms are analyzed and compared by means of Monte Carlo simulations.

R. Diversi, R. Guidorzi, U. Soverini (2004). Frisch scheme-based algorithms for EIV identification. s.l : s.n.

Frisch scheme-based algorithms for EIV identification

DIVERSI, ROBERTO;GUIDORZI, ROBERTO;SOVERINI, UMBERTO
2004

Abstract

In many practical situations the process data are affected by noise on both inputs and outputs. In these contexts, errors–in–variables (EIV) models can be the best choice for identification purposes and several approaches based on these representation are present in the literature. This work refers to one of these methods, the so–called dynamic Frisch scheme. In particular, two different Frisch scheme–based algorithms are analyzed and compared by means of Monte Carlo simulations.
2004
Proceedings of the 12th IEEE Mediterranean Conference on Control and Automation
R. Diversi, R. Guidorzi, U. Soverini (2004). Frisch scheme-based algorithms for EIV identification. s.l : s.n.
R. Diversi; R. Guidorzi; U. Soverini
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/5374
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